THE ROLE OF REGULATORY T CELLS

IN ADULTS IN SOUTH AFRICA WITH

ACTIVE TUBERCULOSIS

Elizabeth Sarah Mayne

A research report submitted to the Faculty of Health Science,

University of the Witwatersrand, Johannesburg, in partial

fulfilment of the requirements for the degree of Master of

Medicine in the Branch of Pathology (Haematology)

Johannesburg, 2008

ii

DECLARATION

I, Elizabeth Sarah Mayne, declare that this thesis is my own work. It is being submitted

for the degree of Master of Medicine in the University of the Witwatersrand,

Johannesburg. It has not been submitted before for any degree or examination at this or

any other University.

Day of , 2009

iii

Dedicated to my husband, Paul and my parents.

And in memory of my sister, Alexandra (1982-2003).

iv

PUBLICATIONS AND PRESENTATIONS

Part of this work was presented as a poster at the Keystone Symposium on HIV

Immunology, March 2007.

v

ABSTRACT

Introduction

Regulatory T cells (Tregs) are increasingly being recognized as key immunological

players in immunosuppression and have been seen to be permissive for certain infections.

Aim

This study aimed to elucidate the role that Tregs play in symptomatic infection with

Mycobacterium tuberculosis (TB), both with and without co-infection with human

immunodeficiency virus type 1 (HIV 1) by quantification of these cells at ex vivo. It was

then attempted to characterise the behaviour of FoxP3 positive cells in culture with

stimulation.

Methods

Peripheral blood mononuclear cells were purified from uninfected controls, patients with

active TB, patients with HIV infection and patients with HIV infection and active TB.

The frequencies of Tregs were assessed by flow cytometry at ex vivo and again after four

days of culture with stimulation with anti-CD3, Purified protein derivative, tetanus toxoid

and HIV peptide superpools (gag and nef). These frequencies were compared between

the four groups of patients. The ability of Tregs and effector T cells to proliferate was

also assessed. Interferon-γ secretion was used as a measure of effector T cell response to

stimulation.

vi

Results

Frequencies of Tregs were significantly reduced in patients with active TB as compared

with HIV infected patients and uninfected controls. Co-infected individuals showed a

broad range of frequencies which were not significantly different from controls. These

frequencies remained stable in culture with the exception of those individuals infected

with HIV who showed a decline in the frequency of those cells expressing FoxP3 over

the period. Cells expressing FoxP3 were not anergic and responded to stimulation. HIV

specific proteins, in addition, resulted in specific effects on the Tregs with a positive

interferon response to gag correlating with increased Treg frequencies and FoxP3

expression in CD4+ T cells correlated with the proliferative response of CD4+ T cells to

Nef in HIV infected individuals.

Conclusions

This study shows significant differences of frequencies of FoxP3 positive producing cells

in the peripheral blood at ex vivo in patients with active TB. The function of these cells in

this population is uncertain and further functional data and long-term clinical follow-up is

required. In addition, the frequencies of these cells remained constant over time and

showed proliferative response to stimuli (most notably CD3) suggesting that these cells

may be generated in the periphery.

vii

ACKNOWLEDGEMENTS

This study was funded by the South African AIDS Vaccine Initiative, the Wellcome

Trust, the NHLS and the Elizabeth Glazer Paediatric AIDS Foundation International

Leadership Award.

Thanks for help training and advice, go to the staff at the NICD especially Drs Stephina

Nyoka and Sharon Shalekoff who gave invaluable advice on the design of the flow

cytometry assays. Thanks go to Dr Leslie Scott and Ms Lara Vallet for assistance with

the CD4 testing on all of the patients and to Dr Scott and Prof Debbie Glencross for their

advice.

The study would not have been possible with the kind donation of blood by the patients

and the help of the clinicians at various sites including Dr Francois Venter and the staff at

the Antiretroviral Clinic at Johannesburg Hospital, staff at the Hillbrow Primary Health

care clinic and staff at the 8th Avenue and East Bank Clinics in Alexandra.

For his unfailing good humour in the face of a mountain of statistics and for helping me

to make sense of them, a huge debt of gratitude goes to Mr Anthony Mayne.

Thank you to both my supervisors Prof Wendy Stevens and Prof Clive Gray for their

continuing support and advice and for being patient with the delays in completion of the

work.

Finally, for all their help and support, thanks go to Dr Melinda Suchard and Ms Victoria

Eastham who helped with data collection and who have utilized different components of

viii

the database in their own research work. I have learnt a fortune from both of you and

could never have done it without you.

ix

TABLE OF CONTENTS

Page

DECLARATION

DEDICATION

PUBLICATIONS AND PRESENTATIONS

ABSTRACT

ACKNOWLEDGEMENTS

TABLE OF CONTENTS

LIST OF FIGURES

LIST OF TABLES

ii

iii

iv

v-vi

vii-viii

ix-xi

xii-xiii

xiv

1. INTRODUCTION

1.1. Basic Immunology 1-4

1.2. Characterisation of the Regulatory T cell 4-5

1.3. The Ontogeny of Regulatory T cells 5-8

1.4. The Function of Regulatory T cells 8-12

1.5. The role of Regulatory T cells in human disease 12-16

1.6. Mycobacterium tuberculosis: the immune response and basic bacteriology 16-19

2. AIM

2.1. Primary aim 20

2.2. Secondary aim 20-21

3. METHODS

3.1. Patient selection 22-25

x

3.2. Isolation of peripheral blood mononuclear cells 25

3.3. Cell cultures and stimulation 25-27

3.4. Intracellular cytokine staining for interferon gamma 27-28

3.5. Intracellular staining for FoxP3 28-29

3.6. Carboxyfluorescein succinimidyl ester (CFSE) staining 29-30

3.7. Acquisition 30

3.8. Analysis and gating strategies 31

3.9. Statistical analysis 31

4. RESULTS

4.1. Ex vivo Treg frequencies 32-33

4.2. Alteration in Treg frequencies after culture 34-38

4.3. Correlation of GITR, CTLA-4 and CD25 high as markers of Tregs 38-40

4.4. CFSE staining and interferon gamma secretion 41-45

5. DISCUSSION

5.1. Ex vivo regulatory T cell frequencies are significantly lower in patients with

tuberculosis disease than in normal controls and in patients with HIV infection.

46

5.2. Regulatory T cells are not anergic in culture 47

5.3. Neither GITR nor CTLA-4 are reliable markers for assessment of Tregs 47-49

5.4. Tregs can respond to specific stimuli 50

5.5. CD4+ T cell proliferation correlates with interferon-gamma production in

CD4+ T cells

50

5.6. HIV specific peptides exert an immunomodulatory role in Tregs with

prolonged exposure

50-51

xi

6. Conclusion 52-54

7. Appendix – Tables of Statistical results 55-60

8. References 61-71

xii

LIST OF FIGURES

Page

1.1 T cell ontogeny and T cell subsets. T cells proliferate in the bone marrow and

move to the thymus where they undergo a process of conditioning which results in

negative selection of self reactive T cells.

3

4.1 A comparison of ex vivo Treg frequencies at ex vivo with no stimulation

(significantly increased in HIV infected individuals p<0.001)

32

4.2 Comparison of FoxP3 expression (y axis) against CD25 expression in CD3+

CD4+ T lymphocytes ex vivo in uninfected (a), TB disease (b) and HIV infected

(c) individuals

33

4.3 Frequencies of Tregs after 4 days of culture with no stimulation. 34

4.4 A comparison of the effect of anti-CD3 stimulation on Treg frequency after 4

days of culture (significant differences compared with ex vivo for control

population, HIV infected population and patients with TB disease p<0.01,

p<0.006 and p<0.001).

35

4.5 Response to PPD stimulation at day 4 by Treg frequency in an HIV infected

individual compared with an unstimulated control (12.7% vs 8.81%)

36

4.6 A comparison of the effect of stimulation with Gag superpool on Treg frequency

in the 4 patient populations after 4 days of culture – Gag stimulation resulted in a

significant increase in frequency in the HIV infected patients compared with other

patient populations (p<0.05).

37

4.7 A comparison of the effect of stimulation with Nef superpool on Treg frequency

in the 4 patient populations after 4 days of culture – Nef stimulation appeared to

37

xiii

reduce the frequency of cells expressing FoxP3 in the uninfected controls but this

trend failed to reach significance

4.8 A comparison of CD25 high staining, CTLA-4 staining and GITR staining in an

individual with active TB ex vivo – the correlation amongst these markers and

between these markers individually and FoxP3 was unreliable.

39

4.9 Regression of CD25hi, CTLA-4 and GITR expression on FoxP3 failed to show a

significant correlation with FoxP3 for any patient group

40

4.10 CFSE dye dilution showing significant proliferation of CD3 + CD4+ FoxP3+T

cells in response to anti-CD3 stimulation.

42

4.11 Interferon- gamma expression at day 1 by CD4+ T cells in an individual with HIV

and active TB in response to no stimulation, anti-CD3, Gag superpool and Neg

superpool (CD4+ T cells on the y-axis and IFN-γ on x-axis). A significant

response is shown to the HIV specific peptides and to anti-CD3 by the non- CD4+

T cells (defined by their expression of CD3)

44

4.12 A regression of FoxP3 on IFNγ expression in CD4+ T cells in uninfected

individuals with Gag stimulation showing a significant correlation

(p<0.001)

45

4.13 A linear regression of CFSE low on FoxP3 in CD4+ T cells in HIV infected

individuals showing a significant correlation between proliferation and Treg

frequencies with Nef stimulation after 4 days of culture (p<0.016)

45

xiv

LIST OF TABLES

Page

3.1 Demographic characteristics of patient populations 23-25

4.1 Treg frequencies following stimulation compared with unstimulated cells at day

four for all four classes

55

4.2 CFSE measured proliferation of Tregs to stimulation compared with no

stimulation on day four

56

4.3 Comparison of CFSE measured Treg proliferation in HIV, active TB and HIV

patients with active TB compared with uninfected controls

56

4.4 Correlation between CD4+T cell proliferation and CD4+T cell interferon gamma

secretion

57

4.5 Proliferation of FoxP3+ CD4+ T cells correlated with interferon gamma

production by CD8+ T cells

58

4.6 FoxP3 frequency correlated against CFSE measured proliferation and secretion

of interferon gamma by CD4+ T cells

59-60

1

1.0 Introduction:

1.1 Basic Immunology

The immune system is the body’s defence against infectious organisms. It is classically

divided into two distinct systems – the innate immune system and the adaptive immune

system. The innate immune system, the first line of defence, is non-specific and responds

to pathogen-associated molecular patterns. Pathogen-associated molecular patterns are

distinctly foreign molecular signatures which include double-stranded RNA and

prokaryoytic structural proteins like flagellin amongst others (Gordon 2002, Stenger and

Modlin 2002). Some of the receptors which detect these foreign signatures are the toll-

like receptors and the complement protein cascade. Cells which are intimately involved

with the innate response to infection include phagocytes (macrophages, neutrophils and

dendritic cells) and innate-like lymphocytes (natural killer cells, natural killer T cells and

B1 B lymphocytes). These cells are responsible for priming the adaptive immune

response and introducing the foreign organism to the lymphocytes (Bendelac et al 2007,

Kronenberg and Havran 2007)

Lymphocytes are the key effector cells of the adaptive immune response. Two distinct

types of lymphocytes are recognized – B cells and T cells. B cells are responsible for the

humoral or antibody-mediated immune response. Antibodies are small protein molecules

which are produced to respond to a small signature called an antigen. Once antibodies

2

bind to an antigen, they can trigger a series of processes which include stimulation of

phagocytosis (opsonisation), stimulation of a cytolytic natural killer cell response

(antibody dependent cellular cytotoxicity) and activation of the complement cascade

which in itself results in phagocytosis, recruitment of immune cells to the area and

cytolysis.

T lymphocytes are the central cell population of the adaptive immune response. T

lymphocytes are divided into those which express the protein, CD4, on their cell surface

and those which express the protein, CD8, on the cell surface (Figure 1.1). CD4+ T cells

are helper T cells – they coordinate the immune response predominantly by the secretion

of humoral cellular signals called cytokines. CD4+ T cells are classically divided into Th1

cells which stimulate primarily a cytotoxic response and Th2 cells which secrete

cytokines which prime a B cell (antibody) response. In addition, regulatory classes of

CD4+ T cells have been described including Th3 and Tr1 cells which are thought to

secrete predominantly immunosuppressive cytokines (transforming growth factor β and

interleukin 10 respectively). CD8+ T cells are cytotoxic T cells – they recognize cells

with an internal infection through a unique molecule called the Major Histocompatibility

Class (MHC) I molecule and cause them to undergo apoptosis or kill them through the

perforin-granzyme pathway. (Lanzavecchia and Sallusto 2001). Recently, a third class of

effector CD4+ T cells with proinflammatory properties, has been described which

develop under the influence of the cytokines IL-6 and IL-23 and produce the cytokine IL-

17 which has been implicated in the development of autoimmune disease.

3

The immune system is necessarily under tight regulation in all stages of an immune

response. The innate immune system, for example, is regulated in its zymogenic

complement cascade through a number of complement inhibitors which work in an

analogous way to the anticoagulants in the coagulation cascade. In addition, many of the

Figure 1.1

T cell ontogeny and T cell subsets. T cells proliferate in the bone marrow and move to the

thymus where they undergo a process of conditioning which results in negative selection

of self reactive T cells.

Double negative

thymocyte(expresses

neither CD4 nor

CD8)

CD25 + CD44+ Pre-TCR

CD4+ CD8+

CD4

Effector CD4+ T cells

Th1 cytokines e.g. IFNγ

Th2 cytokines e.g. IL4

Th1 T cell

Th2 T cell

Predominantly cell-mediated response against intracellular pathogens Stimulates cytotoxic cell killing by antigen –specific CD8+T cells

Predominantly humoral response against extracellular pathogens. Aids B lymphocytes to produce antibodies.

Regulatory CD4+ T cells

Th3 T cell

Tr1 T cell

Treg Naturally occurring and inducible cells expressing FoxP3

Regulatory CD4+ T cells secreting Transforming growth factor β

Regulatory CD4+ T cells secreting the cytokine IL10

CD8

CD8 effector cell

CD8 suppressor cell

Th17 T cell

Implicated in autoimmune disease. Secretes proinflammatory cytokine IL17 IL6, IL23

4

immune system cell populations contain regulatory subsets. For example, natural killer

cells expressing no or dim CD56 tend to be regulatory rather than cytotoxic (Fan, Yang

and Wu 2008). It is appropriate, therefore that the cell which coordinates the adaptive

immune response, the helper T cell, receives tight regulation.

1.2 Characterisation of the Regulatory T cell

The Regulatory T lymphocyte appears to play a prominent role in regulation of the

immune system. Although the existence of suppressor cells in the immune system has

long been postulated, it was only in a recent study by Sakaguchi et al (2000) that a

method for further characterizing a population of putative regulatory T cells utilizing the

markers CD4+ (a co-receptor for the T cell receptor utilized in stimulation) and high

expression of CD25 (the gamma chain of the IL2 receptor), was described. Later, a

transcriptional factor was identified, the Forkhead Box P3 factor or FoxP3 (a member of

the winged/helix transcription family) which appears to be central to the activation,

identification and function of the regulatory T cell (Hori, Nomura and Sakaguchi 2003,

Ramsdell and Ziegler 2003). This factor was first identified in the Scurfy mouse. The

Scurfy mouse, analogous to humans with the IPEX syndrome (immune dysregulation,

polyendocrinopathy, enteropathy, X-linked syndrome) presents with a disease complex of

uncontrolled lymphoproliferation, immune paresis and autoimmune phenomena, which is

generally fatal (Hori, Nomura and Sakaguchi 2003, Hori and Sakaguchi 2004). Some of

the postulated mechanisms of action of this factor include its direct effects on T cell

5

receptor signalling and its inhibition of other transcription pathways like the nuclear

factor of activated T cells (NFAT) pathway.

Although FoxP3 has been described as best characterising the Treg population, it has

limitations. FoxP3 measurement, by flow cytometry or PCR, requires permeabilisation of

the cell. In addition, studies have suggested that FoxP3 (like CD25) may be upregulated

as a marker of activation on human T cells as distinct from mice (Morgan et al 2005)

albeit at lower levels than regulatory T cells and very temporarily (Allan et al 2007). This

has recently been disputed – the suggestion being that co-culture of FoxP3+ and FoxP3-T

cells confounds data because the regulatory population is overwhelmed by the FoxP3-

population and that these cells which are FoxP3+ ex vivo have clear suppressive

functions (Pillai et al 2008). Because of the controversy existing regarding the

characterisation of regulatory T cells in humans, surrogate molecules are currently under

evaluation including Cytotoxic T lymphocyte associated factor-4 (CTLA-4) and

Glucocorticoid-induced tumour necrosis factor-like receptor (GITR) amongst others

(Wing et al 2008, Yong et al 2006).

1.3 Ontogeny of Regulatory T cells

CD4+ CD25+ thymocytes display full regulatory T cell activity – the thymus hence

appears to be an important nidus for Treg development (Thompson and Powrie, 2004). In

addition, neonatal thymectomy is associated with a similar clinical picture to IPEX as a

6

result of Treg deficiency (Chatila 2005). The ability of Tregs to undergo development

outside the thymus remains controversial (Bachetta et al 2005).

The development of this population appears to be strongly IL2-dependent as evidenced

by the expression of CD25 and further confirmed by the proliferative response of Tregs

following the administration of IL2 (Ahmadzadeh and Rosenberg 2006). Tregs have

previously been described as an anergic population, which are unable to proliferate in the

absence of the IL-2 (Hori and Sakaguchi, 2004) in vitro. Tregs could thus be a population

that develops in response to an interaction between the T cell receptor and the MHC II

antigen expressing self-antigens. Tregs cannot develop in recombination-activating gene

(RAG) deficient mice (who lack a T-cell receptor) suggesting that the T cell receptor is

vital for the development of this population of cells. Mice with MHC II expression

limited to the thymic cortical epithelium (K14-Aβb mice) appear to be able to develop a

functional Treg population suggesting that MHCII interaction outside of the thymus plays

no major role in Treg maturation. Other studies have suggested that the thymic medullary

epithelium may also play a role (Maggi et al 2005). The data support a high-affinity

TCR-MHC interaction at avidities associated with deletion. Tregs cells appear to be

subjected to positive selection in the thymus selecting autoreactive cells. They are also

subject to negative selection as the thymus selects against cells which are strongly

reactive to self-antigens (Hori and Sakaguchi, 2004, Chatila 2005). TCR variability in the

population is as marked as in CD4+ CD25- T cells suggesting that the population does not

represent a recently activated set of lymphocytes (Fujisima et al 2005, Bosco et al 2005)

An increased strength of the TCR signal is associated with a decreased suppressive

7

activity of Tregs (Baecher-Allan, Wolf and Hafler 2005). Although the role of self-antigens

is probably paramount, it is certain that Tregs can recognise pathogenic antigens (notably

L. major, an intracellular protozoan) through their T cell receptors - whether these

pathogens are merely cross-reacting with similar self-antigens or play a role in Treg

ontogeny is unclear (Hsieh et al 2004).

Studies in B7 deficient and CD28 deficient mice (NOD mice), which are unable to

present antigen effectively to T cells because of an absence of co-stimulatory molecules,

showed a marked numerical decrease in the population of Tregs, which suggested that

these stimulatory pathways are necessary in the development of this population. These

mice were prone to the development of diabetes, which was reversed by Treg transfusion

(Salomon 2000). Nevertheless, the strength of the TCR signal appears to have an inverse

relationship with the development of the Treg population (Baecher-Allan, Viglietta and

Hafler 2005). Antibodies targeted at CD28 have strongly upregulated Treg production and

have shown some promise in the context of animal models of autoimmunity (Beyersdorf

et al 2005).

TGFβ appears to have a central role in the development of Tregs, which is now only

beginning to be elucidated. It upregulates the expression of FoxP3 (Fantini et al 2004, Le

et al 2005) and indirectly recruits the NFκB and MAP kinase signalling pathways and in

some cases can attenuate the signalling pathways activated by other molecules e.g.

lipopolysaccharides (LPS). Maintenance of the Treg population, as well as being

dependent on IL2, requires TGF-β, which appears to maintain the levels of FoxP3

8

peripherally and plays an important role in their development (Fantini et al 2004). Toll-

like Receptor proteins which play a crucial role in the innate system appear to be

important in the development of Tregs (especially TLR5). Tregs appear to over-express

some toll-like receptors and the ligation of TLR5 has been shown to increase the

suppressive activity of the cells (Crellin et al 2005).

Although the Th1 response appears to be the primary target (through the CD4+ T helper

cell), Tregs also appear to inhibit several other important immune responses. The Th2

response may be inhibited through a contact-dependent mechanism on peripheral B

lymphocytes– the Treg may directly inhibit B-cell somatic hypermutation and class-

switch (Lim et al 2005). Studies in mice that overexpress FoxP3 have also suggested that

the inhibition of the B lymphocytes may also be related to the inability of CD4+ cells

adequately to direct the antibody response in mice (Kasprowicz et al 2003)

Tregs appear to affect other antigen-presenting cells such as monocytes/macrophages

that appear to downregulate their co-stimulatory molecules in response to Tregs and show

reduced secretion of proinflammatory cytokines (TNF-α and IL-6) in response to

stimulation with lipopolysaccharide (Taams et al 2005). Tregs also maintain dendritic

cells in an inactive state in the absence of a large population of activated T cells or large

amounts of antigenic stimulation (Serra et al 2003).

9

1.4 Function of Regulatory T cells

Regulatory T cells appear to have multiple functions associated both with the suppression

of the immune response and paradoxically with its activation (in the interaction of Tregs

with H. pylori and Leishmania major infection, these cells appear to play a role in a

memory response recruiting cells to the environment – Thompson and Powrie 2004). The

function of the Treg population could be characterised as a dominant tolerance

mechanism – self-reactive T cells can become anergic in the thymus owing to the absence

of a survival signal but Tregs actively destroy this population. (Sakaguchi 2000, Graca et

al 2005).

1.4.1 Putative cell-contact mediated mechanisms of suppression.

Stimulation of Tregs in vivo resulted in an increase in granularity and increased binding

of antibodies against granzyme but not granzyme B (Grossman 2004). Furthermore,

inhibitors of the perforin pathway (e.g. EGTA and concanamycin A) seem to limit the

cytotoxic capacity of Tregs (Grossman 2004). This argues that the Tregs utilise a cell-

mediated cytotoxic process similar to that utilised by the Natural Killer Cell population of

the innate immune system. In addition, it has been shown that Tregs express CD39, an

ATPase, which neutralises the proinflammatory ATP in local inflammatory responses

and generates adenosine which inhibits T effector cells through a cAMP mediated

mechanism. This suppression results in decreased production of IL-2 by effector T cells

(Bynoe and Viret 2008)

10

The role of CTLA-4 is uncertain. It has been suggested that CTLA-4, which binds

strongly to B7 molecules (more strongly than CD28), may result in competitive inhibition

– effector T cells can no longer access the co-stimulatory molecules (Sato et al 2005).

CTLA-4 also triggers the induction of indoleamine 2,3-dioxygenase which catalyses

tryptophan conversion into kinurenins, which are immunosuppressive (Maggi et al 2005).

Recently, knockout studies in mice suggest that CTLA-4 function is integral to the

function of Tregs but it is uncertain whether this translates to human Treg populations

(Wing et al 2008).

Tregs also appear to inhibit a Th2 response through a contact-dependent mechanism on

peripheral B lymphocytes post-activation – this suppression appears to be linked to an

immunoglobulin class switch (Lim et al 2005). Interestingly, mice with a FoxP3 mutation

resulting in a gain of function failed to express an adequate immunoglobulin response in

vivo and showed markedly disrupted splenic architecture yet the function of the isolated

B cells in vitro appeared to be normal. This was probably related to the inability of the

CD4+ T cells to secrete the necessary cytokines required for a class switch to IgG or IgE

(INF-γ and IL4) and a failure to upregulate membrane ligands CD40 and CD69

((Kasprowicz et al 2003). Tregs also affect other antigen-presenting cells –

monocytes/macrophages downregulate their co-stimulatory molecules in response to

Tregs and show reduced secretion of proinflammatory cytokines (TNF-α and IL-6) in

response to stimulation with LPS (Taams 2004). Tregs also maintain DCs in an inactive

state in the absence of a large population of CD154+ CD4+ CD25- T cells or large

amounts of antigenic stimulation (Serra et al 2003).

11

The Glucocorticoid-induced TNF receptor-related protein (GITR) has a controversial role

in the function of Tregs. Mouse studies suggest that the production of GITR ligand

(GITR-L) by antigen presenting cells (by superantigen e.g S. aureus ) results in the

downregulation of the Treg response (Cardona et al 2006).

A final marker, which is constitutively expressed on Tregs, is CD137 (4-1BB) and

ligation to CD8+ T cells may have a role to play in their suppressive activity. In 4-1BB

knock-out mice (a mouse model constitutively lacking CD137), however, Treg function

appears not to be seriously compromised (Maerten et al 2005).

1.4.2 Cytokine secretion

A co-stimulatory pathway may involve secretion of cytokines – especially IL10, which is

a potent downregulator of the immune response. This cytokine is secreted by other

regulatory cells, including Th3 cells and Tr1 cells; but whether it plays a role in the

function of naturally occurring Tregs is uncertain. (Vieira et al 2004). It was noted that

FoxP3-transduced cells produced more IL10 mRNA but the exact reason remains unclear

(O’Garra 2005). Furthermore, Tregs appear to dowregulate the secretion of other

cytokines, particularly IFN-γ and TNF-α (although possibly not in the early stages of the

suppressive response – Khazaie and Von Boehmer 2006). The downregulation of

cytokine expression occurs both with and without suppression of proliferation of effector

12

T cells (Kelsen et al 2005). These are known functions of IL-10 further highlighting its

possible importance in Tregs.

1.5 The role of Tregs in human disease

A strong Treg response can be beneficial in some human disease and detrimental in

others.

Regulatory T cells play a fundamental role in the suppression of autoreactive T cells.

They appear to function both in draining lymph nodes (attempting to prevent the

activation of autoreactive cells) and in target organs. They migrate to the target organs as

the disease progresses with eventual acquisition of adhesion markers. The Tregs are

targeted at specific autoreactive cells – if there is no target effector T cell population

directed at a specific antigen (like the pancreatic β islet cells) then Tregs have no function

(Tonkin et al 2008). In the non-obese diabetic (NOD) mouse model of diabetes, for

example, endocrine but not exocrine disease is halted, suggesting that the initial

stimulation of the Treg is vital for its eventual function (Bluestone and Tang 2005).

Defects in FoxP3 have been discovered in multiple autoimmune diseases, suggesting that

a primary pathology in Treg function or absolute number may be playing a role in the

pathogenesis of the autoimmune disorders listed below.

13

Studies on mouse colitis as a model for inflammatory bowel disease demonstrate

mutations in the FoxP3 gene which appear to be responsible for poor Treg function and

decreased numbers of Tregs in the inflamed mucosa (Kelsen et al 2005)

The link between IPEX (the disease caused by congenital absence of the FoxP3 gene) and

both eczema and food allergies suggests that these allergies may linked to primary Treg

defects that both these diseases individually may be related to a primary Treg defect.

Atopic dermatitis has been linked to abnormal T cell function in the presence of a

superantigen (Thompson et al 2004) and the use of cyclophosphamide to treat contact

dermatitis resulted in a paradoxical increase in the reaction owing to the effects on the

Tregs (Ikezawa et al 2005). Mucosal tolerance in mice has been linked to the

development of a specific set of Tregs for the antigen. (Winkler et al 2006)

Experimental autoimmune encephalomyelitis (EAE) is the mouse model for human

demyelinating multiple sclerosis (anti-myelin basic protein). Studies in EAE mice have

suggested that this disease is also related to poor Treg function and therapies targeting

Treg proliferation rather than purely T cell depletion appear to hold promise for the

treatment of this disease in humans (Kelsen et al 2005, Duplan et al 2006). These

therapies include the use of oestrogen which has been shown to have a stimulatory effect

on FoxP3 and specific TCR peptides. Another novel therapy is LF-15-0195, which also

causes the Treg population to expand (Duplan et al 2006). Studies have suggested that

Tregs may not be responsible for the primary remission of the disease but that secondary

remissions do not occur in mice with EAE and ablated Tregs (Gartner et al 2006).

14

The pathogenesis of Rheumatoid arthritis appears to be linked to the inability of Tregs to

control the secretion of inflammatory cytokines by CD4+ T cells. Thus, although the

absolute numbers of Tregs are normal in most subjects, the disease can be markedly

improved by adding a suppressor against cytokine secretion like TNF-α. Higher numbers

of Tregs in joint fluid is linked to an improved prognosis in Rheumatoid Arthritis (Chatila

2005).

Clinical improvement in asthmatics which is associated with treatment with

glucocorticoids is associated with an increase in IL10 secretion, FoxP3 mRNA levels and

with the upregulation of secretion of TGF-β (Karagiannidis et al 2004, Till et al 2004)

Some of the disadvantageous effects of Tregs include their propensity to facilitate

evasion of the immune system. Two primary pathological processes, namely malignancy

and infection, have been shown to utilise an expanded regulatory T cell population to

suppress specific cytotoxic responses. In tumours, a strong cell-mediated immune

response is associated with improved survival and a less aggressive phenotype. It is

therefore not surprising that many tumours specifically and non-specifically activate

Tregs as a strategy for immune evasion. Higher levels of Tregs have been found in many

haemopoietic malignancies. Non-Hodgkin’s Lymphomas appear to secrete chemotactic

factors for Tregs including CD122 so that there is a markedly elevated population

throughout the body (approximately 17% Tregs were found in diseased nodes and 7% in

non-diseased nodes as opposed to the normal 2-5% - Yang et al 2006). Certain T cell

15

leukaemias express a Treg phenotype, which may be linked to a more aggressive course

although the exact functional significance in these cells remains unknown (Chen et al

2006). Gastric and oesophageal carcinomas show an increased size of the population of

Tregs compared with healthy donors; this correlated positively with increased stage of the

tumours and with the risk of tumour recurrence (Perrone et al 2008). Higher levels of

FoxP3 mRNA expression correlate with a poorer prognosis in ovarian cancer (Wolf et al

2005). Studies in mice have shown that certain tumours e.g. pancreatic adenocarcinoma

can induce a regulatory phenotype in previously CD25- FoxP3 – CD4+ cells. Any

immunomodulatory treatment, for example with dendritic cells focused at cancers (as is

being considered for melanoma), may have to be associated with immunosuppressive

therapy in order to eliminate pre-existing population of Tregs (Lopez et al 2005). An

example would be the administration of IL-2 which is associated with massive

proliferation of the Treg population (Ahmadzadeh and Rosenberg 2006)

Tregs also limit the response of the immune system to infections. This can result in

infection persistence but may also prevent a neutralising response with loss of antigen-

maintained memory (Gavin and Rudensky 2003, O’Garra 2005). In Leishmania spp.

infections, it has been demonstrated that 50% of the involved T cell populations are Tregs

with failure of the immune response to eradicate the pathogen (Gavin and Rudensky

2003). Certain pathogens are associated with the induction of immature dendritic cells

(DCs), which favours the induction of a regulatory T cell population. Plasmodium

falciparum scavenges CD36, which prevents the maturation of DCs by LPS and studies

have demonstrated that an expanded regulatory T cell population is associated with faster

16

rates of parasite growth (Good 2005, Walther et al 2005). Mannosylated

lipoarabinomannans (immunogenic glycolipids) from Mycobacterium spp. also inhibit

Treg maturation and the secretion of IL-12. Ebstein-Barr virus (EBV) expressing cells

which over-express the Notch ligand, Jagged-1, have been shown to induce the

development of a Treg population that suppresses function and proliferation of effector

cells with possible effector function in transplantation (Vigoroux et al 2003).

1.6 Mycobacterium tuberculosis: the immune response

The estimated prevalence of active infection with Mycobacterium tuberculosis in 2005

was approximately 14 million infected individuals, of which 3, 77 million cases were

based in Sub-Saharan Africa with 340 000 new cases in South Africa alone in 2004

(World Health Organisation). Owing to the link between TB and HIV, the epidemic of

tuberculosis continues to escalate.

17

In high prevalence settings, like Sub-Saharan Africa, many individuals are infected with

Mycobacterium tuberculosis, but not all develop active disease. The WHO Global

tuberculosis control - surveillance, planning, financing report (2005) indicates that 1.7

billion people are infected with TB worldwide. Latent tuberculosis is defined by a

positive skin induration to purified protein derivative in the absence of signs or symptoms

or typical radiological changes (Jasmer et al, 2004). Latent tuberculosis represents a

treatment dilemma. For this reason it is important to define distinguish active tuberculous

disease from asymptomatic infection and the correlates of protection.

The host cell for the mycobacterium is the macrophage. In order to survive within the

phagosome, the bacterium must subvert the host immune system. The organism gains

access to the macrophage through the complement receptor 3, which prevents

proinflammatory activation of this cell (Houyen, Nguyen and Pieters 2006). One of the

key strategies utilized by the bacillus is inhibition of fusion of the phago-lysosome. The

mycobacterium appears to disrupt the essential signaling sequence which enables fusion

of the early and late endosome - this includes the secretion of substances which mimic

host signal transduction molecules, in particular protein kinase G (Walburger et al 2004)

and inhibition of calcium signaling by inhibition of the production of sphingosine-1

phosphate (Thompson et al 2005). Mycobacteria also inhibit the expression of proteins

with the FYVE domain (a specific zinc finger pattern) including early endosome

autoantigen 1 (EAA-1) and hepatocyte growth-factor regulated tyrosine kinase substrate

(Gruenberg and Stenmark 2004) – these proteins are permissive of fusion of the phago-

lysosome. Other immunoevasive strategies include resistance against nitric oxide and its

18

toxic intermediaries and prevention of antigen presentation by attenuating the expression

of HLA class II molecules (Chan and Flynn 2004).

One of the most important cell populations in the control of tuberculosis infection is the

CD4+ T cell population – it is clear that an intact CD4+ T cell population correlates with a

better outcome as studies in patients with compromised helper cell populations have

shown including those with HIV infection (North and Jung 2004, Kaufmann 2005).

Absent levels of Th1 cytokines (interferon-γ and IL12) are associated with an inability to

control tuberculosis disease (Flynn et al 1993, Cooper et al 1993, Cooper et al 1997).

This suggests that the regulatory T cell population may possibly have a pivotal role in

determining the outcome of the disease process by inhibiting a TB specific CD4+ T cell

response. Currently, the role of Tregs is uncertain in the pathogenesis of tuberculosis. A

small pilot study suggested that the numbers of Tregs are increased in active tuberculosis

disease (Guyot-Revol et al 2006). These preliminary findings were confirmed by further

studies (Hougardy et al 2007, Roberts et al 2007). These cells may aid the bacterium (in

addition to the mechanism described above) in immune evasion. Further investigations

(Chen et al 2007) suggest that regulatory T cells, as defined by their expression of CD4,

CD25 and FoxP3 are increased in absolute number and frequency in the blood of patients

with active tuberculosis which compared with uninfected controls and patients with latent

tuberculosis. The effects of these cells appear to be diverse including secretion of IL-10

and suppression of tuberculosis specific interferon-γ secretion (Chen et al 2007). It seems

unclear as to the role of these cells in suppression of infection. Studies in mice that have

19

had preferential depletion of the FoxP3-expressing CD4+ T cell population showed a log

reduction in the colony forming units of Mycobacterium tuberculosis (Scott-Browne et al

2007). In addition, adoptive transfer of FoxP3 expressing CD4+ T cells into mice resulted

in suppression of a tuberculosis-specific effector CD4+ T cell response (Kursar et al

2007).

Infection of a patient with HIV and active tuberculosis disease further complicates studies

of immune regulation in South African populations. It is estimated by the 2005 report by

UNAIDS that 60% of patients with tuberculosis infection are co-infected with the virus

(www.unaids.org). HIV infection itself has been associated with multiple effects on the

Treg population. Depletion of CD25+ cells from a PBMC population results in massive

upregulation of IFN-γ secretion by the remaining T cells suggesting that this population,

even in HIV positive individuals, is directly responsible for suppressing function of HIV

specific CD4+ and CD8+ T cells(Nixon, Aandahl and Michaelsson 2005). This may be

beneficial in downregulating the immune activation which may be partially responsible

for CD4+ T cell apoptosis and depletion (Oswald-Richter et al 2004, Eggena et al 2005).

Nevertheless, because this subset expresses the co-receptor CCR5 and the CD4 molecule,

they are highly susceptible to infection and are also susceptible to the cytotoxic effects in

vitro (Chase et al 2007, Oswald-Richter et al 2004). In addition, their effect on HIV

pathogenesis in vivo remains to be elucidated.

20

2.0 Aim

2.1 Primary Aim

The primary aim of this study was to quantify the number of Tregs, expressing CD25 and

intracellular FoxP3 in patients with active tuberculosis, patients with HIV infection alone

or patients with HIV infection and active TB and to compare these to healthy controls, in

order to determine whether this population of cells could be contributing to the

pathogenesis of HIV infection or tuberculosis disease by suppressing the immune

response to these infections.

2.2 Secondary aims

The secondary aims of the study included elucidating the ability of Tregs to proliferate in

response to both antigen specific and non-specific stimulation in patients with infections

mentioned above. It has been suggested that only centrally produced regulatory T cells

express FoxP3 and that these cells are anergic. Adult patients with depletion of CD4 T

cells would therefore be unable to regenerate their regulatory T cell population.

This was compared with the ability of CD4+ and CD8+ T cells which did not express

FoxP3 to secrete interferon gamma (IFN-γ) and to proliferate in response to the same

stimulation in culture in order to demonstrate a possible regulatory phenotype in co-

culture in the absence of formal depletion studies.

21

The study also aimed to explore the use of additional surface immunophenotypic markers

of regulatory T cells including CTLA-4 and GITR and to compare them to FoxP3 in

order to evaluate their utility as possible surrogate markers for this population.

22

3.0 Methods

3.1 Patient selection

Patients were sourced from the Johannesburg Hospital, Hillbrow Primary Health Clinic

and the Alexandra Primary Health Care Clinics. Each patient gave full informed consent

and the study was approved by the Ethics Committee of the University of the

Witwatersrand (Ethics number M060313). Up to 60 ml of blood was collected from a

peripheral vein using the vacutainer system and anticoagulants: acid citrate dextrose

(ACD) and Ethylenediamine tetra-acetic acid (EDTA) (Table 3.1)

HIV infected group

The patients with documented HIV infection (n=10) were sourced from the Hillbrow

Wellness Clinic and the Johannesburg Hospital (both the anti-retroviral clinic and the

wards). The diagnosis had been made by the managing physicians using a Determine

HIV-1/2 rapid tests (Abbott Laboratories, USA) and confirmed in the majority of patients

by a fourth generation ELISA (Abbott Laboratories, USA). The patients were

antiretroviral drug naïve at time of enrolment and were not taking anti-tuberculous

chemotherapy. They had no obvious clinical symptoms and signs of active tuberculosis.

A small subpopulation (N=3) had bone marrow trephine biopsies which were negative

for the presence of TB granulomata.

23

Active tuberculosis group

The patients with active Mycobacterium tuberculosis infection (n=14) were diagnosed

microbiologically by the presence of acid-fast bacilli in the sputum. These patients were

sourced primarily from the Johannesburg Hospital. The patients with HIV co-infection

(n=9) were anti-retroviral drug naïve at enrolment. The diagnosis of HIV infection was

made in a similar manner to that described above. No patient had taken more than 2 doses

of anti- tuberculous chemotherapy at the time of collection of the samples.

Uninfected group

The uninfected controls (n=10) were sourced from clinically well hospital and laboratory

staff. The samples were tested anonymously after collection for HIV infection using the

Abbott determine HIV rapid test. No results of the testing were revealed to the

participants.

Table 3.1: Demographic characteristics of patient sub- populations

Patient group Ethnic group (B=black,

C=coloured, I=Indian,

W=white)

Age group (1<20yrs,

2 =20-29yrs; 3=30-

39yrs; 4=>40yrs)

Gender (M=male;

F=female)

CD4 count

(x106/l)

Uninfected

population

B

B

B

B

3

3

3

1

F

F

F

M

831

973

1503

671

24

B

B

C

I

B

B

3

2

3

3

3

3

M

F

M

M

M

M

1231

694

950

1332

818

915

HIV infected

population

B

B

B

B

B

B

B

B

B

B

3

2

4

2

3

3

3

3

2

2

F

F

F

F

M

F

M

F

F

F

523

223

118

432

40

169

712

191

219

452

Active TB C 4 M 1503

25

population

B

B

B

B

2

1

4

3

M

F

F

F

743

859

494

801

HIV infected

population

with active TB

B

B

B

B

B

B

B

B

B

B

4

2

2

3

3

3

3

4

3

4

F

F

M

M

M

M

F

F

M

M

8

131

563

1

2

43

59

655

68

258

26

3.2 Isolation of Peripheral Blood Mononuclear Cells (PBMCs)

Peripheral blood mononuclear cells were isolated by a standard Ficoll-Hypaque technique

(Amersham Biosciences, UK). The blood was centrifuged at 2200rpm for 15 minutes

using a Ficoll density gradient. The buffy coat was removed and washed twice with

HBSS (Hank's Balanced Saline Solution – Gibco, Scotland). The cells were then counted

using a Guava Viacount (Guava Technologies, California) according to manufacturer’s

instructions. Those PBMCs which were not stained with CFSE were resuspended in

RPMI 1640 medium with added GlutaMAX and 25mM HEPES (Gibco, Scotland),

supplemented with 10% human serum AB (HuAB) (Gemini Bio-Products, USA) and

0.1% gentamycin (R10) at a concentration of 2 million cells/ml.

3.3 Cell cultures and stimulations

The PBMCs were cultured for 96 hours in 24 well round-bottom plates using appropriate

aseptic techniques. Approximately 2 million cells were cultured in every well. The

culture medium utilized was RPMI 1640 with glutaMAX and 25mM Hepes with 10%

HuAB.

Appropriate stimuli were added to each well. The following stimuli were added:

1. Anti-CD3 (0.1ug/ml) monoclonal antibody – positive control

2. Tetanus toxoid (2ug/ml) – an antigen to which most South Africans have been

exposed in the form of vaccination

27

3. Purified protein derivative (0.01ug/ml – Statens Serum Institut) – a construct of

peptides derived from mycobacterial species

4. Gag clade C peptide superpool (2ug/ml – NMI Peptides, Netherlands) – peptides

of 15 amino acids in length derived from the p55 protein

5. Nef clade C peptide superpool (2ug/ml – NMI Peptides, Netherlands) – peptides

of 15 amino acids in length derived from the negative regulatory factor of HIV

clade C virus

An unstimulated culture was utilized as a negative control.

A separate culture was established in tubes for intracellular cytokine staining for

interferon-γ. An hour after the culture was established, 10ug of Brefeldin A was added.

These samples were incubated with the above-mentioned stimuli and in the culture

medium overnight at a slight angle at 37oc in 5% CO2.

3.4 Intracellular cytokine staining for interferon-γ

Intracellular cytokine staining was performed using a protocol adapted from BD

Bioscience(http://www.bdbiosciences.com/pharmingen/protocols/Intracellular_Cytokine)

The samples were centrifuged in the culture tubes at 1800 rpm for 5 min. EDTA was then

added to the samples which were then incubated for 15 min in the dark at room

temperature. Contaminating red blood cells were lysed with appropriate FACS lysing

solution for 10 minutes and then samples were centrifuged and resuspended. The cells

were then washed with 2ml of FACS wash buffer. The sample was centrifuged and 0.5ml

28

FACS Perm solution was added. The sample was incubated for a further 10 minutes in

the dark and then washed with FACS wash buffer.

The following antibody panel was utilized for staining using concentrations established

during the project by formal antibody titration:

1. CD3 PerCP (15ul) – T cell receptor co-signalling chain

2. CD4 FITC (10ul) – co-receptor for the T cell receptor in T helper cells, acting to

recruit downstream signalling molecules

3. CD8 PE (5ul) – co-receptor for the T cell receptor in cytotoxic T cells, acting to

recruit downstream signalling molecules

4. IFN-γ APC (5ul) – T helper 1 cytokine associated with a pro-inflammatory response

3.5 Intracellular staining for FoxP3

The protocol utilized for FoxP3 staining was that recommended by the manufacturer

(eBiosciences, UK). The samples were stained at 2 time points i.e. after resting overnight

and at 96 hours. Briefly, samples rested overnight were centrifuged within their tubes.

Those samples which had been cultured were harvested by gentle pipetting up and down

and then decanting into standard tubes. The samples were washed with FACS wash

solution, centrifuged at 1800 rpm for 5 minutes and the supernatant was discarded. 1ml of

Fix/Perm Solution (eBiosciences, UK) was then added and the sample was vortexed and

then incubated at 4°C for 30 minutes. Samples were washed with wash buffer and

29

washed a further two times with 2 ml permeabilisation buffer (eBiosciences, UK) with

centrifugation and discard of supernatant after each wash.

Antibodies were then added in the following panels:

1. Panel 1 – CD4 FITC and CD3 PerCP(BD Biosciences, USA), FoxP3 PE

(eBiosciences, UK) and GITR APC (R&D Systems, USA)

2. Panel 2 – CD4 FITC, CD3 PerCP and CD25 APC(BD Biosciences, USA) and

FoxP3 PE (eBiosciences, UK)

3. Panel 3 – CTLA-4 FITC (R&D Systems, USA), CD3 APC, CD4 PerCP (BD

Biosciences, USA) and FoxP3 PE (eBiosciences, UK)

The samples were incubated for 30 minutes in the dark at 4oC. 2ml of Permeabilisation

buffer were then added and the sample centrifuged. This wash step was repeated. The

sample was then resuspended in 200ul of cell fixative (4% paraformaldehyde in PBS).

3.6 Carboxyfluorescein succinimidyl ester (CFSE) staining

The samples to be stained for CFSE were harvested. The cells were placed in a 15ml

Falcon tube and wrapped in foil to avoid light contamination. 2ml of CFSE was added

and the samples were incubated in the dark for 7 minutes. The reaction was then stopped

by adding 4ml ice-cold Fetal Bovine Serum (Gibco, Scotland). The samples were then

washed twice with R10 to remove excess CFSE. PBMCs to be stained with CFSE were

30

transferred to a 15 ml falcon tube wrapped in foil. Additional markers were then added

including FoxP3 PE (eBioscience, UK) and CD3 APC and CD4 PerCP (BD Biosciences,

USA).

3.7 Acquisition

Samples stained with CFSE were acquired solely on a multi-colour LSR II (BD

Biosciences, USA) utilizing FacsDiva acquisition software (BD Biosciences, San Jose).

The IFN-γ and remaining FoxP3 panels were acquired both on the LSR II and on the

FacsCalibur which utilizes CellQuest acquisition software (BD Bioscience, San Jose).

Both the LSR II and the FacsCalibur underwent daily calibration utilising Rainbow

Calibration Beads and FacsComp beads (BD Biosciences, USA) as advised by the

manufacturer. Separate samples were analysed as compensation controls utilizing CD8

FITC, PE, PerCP and APC stained cells which were prepared with the samples.

Compensation was done digitally utilising the computer programme FlowJo (Tree Star,

Stanford USA). A Propodium Iodide control was analysed to assess adequacy of cellular

permeabilisation. Monoclonal antibody controls were utilised to exclude non-specific

binding of fluorescent antibodies.

31

3.8 Analysis and Gating strategies

Analysis was accomplished utilizing FlowJo 6.4.2 software. The samples were analysed

utilizing the negative control to exclude non-specific binding. In the case of the CFSE

analysis, the Mississippi Gating strategy (developed by Mark Connors, of the NIH

Immune Regulatory Laboratory) was utilized to exclude the presence of dead cells.

CD4+T cells were identified initially by separating the lymphocytes on the basis of their

low intracellular complexity (low side scatter), small size (low forward scatter) and then

on the basis of their expression initially of CD3 and then CD4. Gates were established on

the unstimulated and negative (unstained) controls

3.9 Statistical Analysis

The data were analysed utilizing the following statistical tests on the STATA statistical

programme (STATACORP 2005. STATA Statistical Software: release 9. College Station:

STATCORP LP):

1. Testing of the samples for normality and homoskedasticity (equal variances)

using a Shapiro-Wilk (Shapiro and Wilk 1965)

2. A paired t-test for comparison of means

3. Sidak adjustment for multiple comparisons

4. Linear regression and pairwise correlation for the variables of interest.

32

4.0 Results

4.1 Ex vivo Regulatory T cell frequencies

An immediate ex-vivo analysis was performed on samples from all four patient groups to

analyse Treg frequencies. Although previous data (Guyot-Revel et al 2005, Chen et al

2007) has suggested that the frequencies of Tregs are increased in patients with active

tuberculosis, these data show a reduced frequency ex vivo in patients with confirmed

tuberculosis disease (p<0.006) compared with uninfected controls.

010

2030

Per

cent

age

Fox

P3

of C

D3+

CD

4+

1 2 3 4

Comparison by class at baselineRegulatory T cell frequencies

Figure 4.1

A comparison of Regulatory T cell frequencies ex vivo in the 4 groups with no exogenous

stimulation (significantly increased in HIV infected individuals p<0.001 )

The frequencies of Tregs ex vivo were increased in patients with HIV (p<0.001)

compared with uninfected controls, in keeping with the previously described

Control HIV infected TB diseae HIV infected with TB

FREQUENCY OF FOXP3 POSITIVE CELLS Comparison by group at baseline

P<0.001

P<0.006

33

immunoevasive strategy of the virus. There was a broad range of Treg frequencies in the

group infected with HIV with active TB, but the overall frequency was not significantly

different from the controls (Figures 4.1 and 4.2)

FSC-H: FSC-Height <FL3-H>: CD3 PerCP 10ul

100 101 102 103 104

100

101

102

103

104

<F

L2-H

>: F

oxP

3 P

E 5

ul

20.74.22

1.3 3.3

18.676.8

FSC-H: FSC-Height <FL3-H>: CD3 PerCP 10ul

100 101 102 103 104

100

101

102

103

104

<F

L2-H

>: F

oxP

3 P

E 5

ul

14.8

2.89

0.66 2.22

12.684.5

FSC-H: FSC-Height <FL3-H>: CD3 PerCP 10ul

10 0 10 1 10 2 10 3 10 410 0

10 1

10 2

10 3

10 4

<F

L2

-H>

: F

oxP

3 P

E 5

ul

15.5

19.2

11.6 8.19

7.3272.9

Figure 4.2

Comparison of FoxP3 expression (y axis) against CD25 expression in CD3+ CD4+ T

lymphocytes ex vivo in uninfected (a), TB disease (b) and HIV infected (c) individuals

FoxP3 Expression

CD25 Expression

CD25/FoxP3 co-expressing population (20.7%)

CD25/FoxP3 co-expressing population (14.8%)

CD25/FoxP3 co-expressing population (8.19%)

Uninfected control (a)

Individual with TB disease (b)

HIV infected individual (c)

FoxP3 Expression

CD25 Expression

FoxP3 Expression

CD25 Expression

34

4.2 Alterations in Treg frequencies after culture

The samples were cultured for four days in order to assess whether these populations

were anergic in culture. In addition, if, as has been suggested, FoxP3 merely represents

an activation marker, it would be likely that the cells expressing FoxP3 would undergo

apoptosis. There was indeed a significant decline in the frequency of CD4+ T cells

expressing FoxP3 after 4 days of culture in the HIV-infected individuals suggesting that

these cells may have undergone apoptosis although no markers of apoptosis were utilised

to measure this directly. The frequencies with culture remained stable (compared with

frequencies immediately ex vivo) in all other population groups suggesting that there was

no significant proliferation or apoptosis in the absence of stimulation. (Figure 4.3)

05

10

15

2025

Pe

rce

nta

ge F

oxP

3 of

CD

3+ C

D4

+

1 2 3 4

Comparison by class at day 4Regulatory T cell frequencies

Figure 4.3

Frequencies of Tregs after 4 days of culture with no stimulation (no significant change

was noted in frequency except in the group infected with HIV only)

Control HIV infected TB disease HIV infected with TB

FREQUENCY OF FOXP3 POSITIVE CELLS Comparison by group at day 4

35

Anti-CD3, which engages the T cell receptor signalling chain, is a potent T cell stimulant.

In most groups, stimulation with anti-CD3 resulted in a significant proliferative response

and a significant increase in the frequency of Tregs compared with frequencies ex vivo.

The exception was the group of patients who were infected HIV and had active TB

disease who failed to show a proliferative response even to this stimulant. Tetanus

(against which, many of the South African population have been immunised), which was

used as a second positive control, failed to produce a significant proliferative response in

any of the four population groups (Figure 4.4).

020

4060

80P

erce

ntag

e F

oxP

3 of

CD

3+ C

D4

+

1 2 3 4

Comparison by class at day 4 with anti-CD3 stimulationRegulatory T cell frequencies

Figure 4.4

Comparison of the effect of anti-CD3 stimulation on Treg frequency after 4 days of

culture (significant differences compared with ex vivo for control population, HIV

infected population and patients with TB disease p<0.01, p<0.006 and p<0.001

respectively)

Control HIV infected TB disease HIV infected with TB

FREQUENCY OF FOXP3 POSITIVE CELLS Comparison by group with anti-CD3 stimulation

P<0.01

P<0.006 P<0.001

P<0.148

FREQUENCY OF FOXP3 POSITIVE CELLS Comparison by group on day 4 with anti-CD3 stimulation

36

PPD (Staten Serum Institute, Denmark) is a tuberculous protein derivative and was used

in all 4 groups to try to stimulate an antigen-specific response, particularly in the groups

with active tuberculosis. There was, however, no significant response in any population

group. A single HIV positive patient showed a significant response to PPD stimulation at

day 4 (103% increase between PPD stimulation and no control) although the overall

effect on the class as a whole was not significant (Figure 4.5).

2 3 4 5

0

102

103

104

105

<PE

-A>:

Fox

P3

8.185.61

3.65 1.53

6.6588.2

2 3 4 5

0

102

103

104

105

<P

E-A

>: F

oxP

3

12.711.4

5.06 5.85

6.8482.3

Figure 4.5

Response to PPD stimulation at day four by Treg frequency in an HIV infected individual

compared with unstimulated control (12.7% versus 8.18%)

Two HIV peptide pools were utilised for stimulation – a Gag superpool composed of 70

peptides and a Nef superpool composed of 50 peptides (NMI peptides). Both superpools

comprised peptides 15 amino acids in length, with an 11 amino acid overlap. Gag

proteins include the structural proteins of the viral core (capsid, matrix, and nucleocapsid

proteins). Nef (negative replication factor) protein appears to be important in viral

replication and immunomodulation (Pennington et al 1997, Noviello et al 2007, Schindler

et al 2007) although the extent to which the peptide superpool reflects this function is

FoxP3 expression

FoxP3 expression

CD25 Expression CD25 Expression

Unstimulated control HIV infected patient

37

010

2030

Per

cent

age

Fox

P3

of C

D3+

CD

4+

1 2 3 4

Comparisons by class at day 4 with Gag superpool stimulationRegulatory T Cell frequencies

Figure 4.6

A comparison of the effect of stimulation with Gag superpool on Treg frequency in the 4

patient populations after 4 days of culture– Gag stimulation resulted in a significant

increase in frequency in the HIV infected patients compared with the other patient

populations (p<0.05)

05

1015

Perc

ent

age

Fox

P3

of C

D3+ C

D4+

1 2 3 4

Comparisons by class at day 4 with Nef superpool stimulationRegulatory T Cell frequencies

Figure 4.7

A comparison of the effect of stimulation with Nef superpool on Treg frequency in the 4

patient populations after 4 days of culture – Nef stimulation appeared to reduce the

frequency of cells expressing FoxP3 in the uninfected controls but this trend failed to

reach significance

Control HIV infected TB disease HIV infected with TB

FREQUENCY OF FOXP3 POSITIVE CELLS Comparison by group at day 4 with Nef stimulation

FREQUENCY OF FOXP3 POSITIVE CELLS Comparison at Day 4 with Gag stimulation

Control HIV infected TB disease HIV infected with TB

38

uncertain. Gag stimulation resulted in a significant increase in Tregs in the patients

infected with HIV alone (p<0.05 - Figure 4.6). A trend was noted in the uninfected

controls for a decrease in Treg frequencies compared with ex vivo frequencies in response

to Nef stimulation but this failed to reach significance (Figure 4.7). No trend was noted

for a positive or a negative change in Treg frequencies in any other population group.

4.3 Correlation of GITR, CTLA-4 and CD25 high expression as

markers of Tregs

Staining for FoxP3 necessitates permeabilisation of cells (which kills them) – this

makes it difficult to assess function in FoxP3 positive cells. In addition, additional

markers which may be associated with suppressive function have been described on

cells with a regulatory function. For this reason, this study assessed three markers

which have been associated with Tregs and correlated their expression with FoxP3.

Bright expression of CD25 has traditionally been used as a surrogate marker in cases

where the Treg population was needed intact. These data failed to show a significant

correlation between CD25 and FoxP3 either at ex vivo or after culture in any patient

population. Two other putative markers were also assessed in this study – CTLA-4

which is the regulatory ligand for B7 (a costimulatory molecule expressed by

professional antigen presenting cells) and GITR which is a glucocorticoid induced

receptor. CTLA-4 blockade has previously been utilised to promote a

39

proinflammatory response (for example in malignancy – Maker et al 2005). Only

GITR showed a significant correlation with FoxP3 and only in the uninfected control

group at ex vivo (a trend was noted after 4 days of culture but this failed to reach

significance). GITR and CD25 expression levels correlated well at baseline and after

4 days of culture in the uninfected control group, but this was not reproducible in the

other groups. (Figure 4.8 and Figure 4.9)

10 0

10 1

10 2

10 3

10 4

<FL2

-H>:

Fox

P3

PE

5ul

1.38

0.038

1.6 1.15e-3

0.04898.410 0 10 1 10 2 10 3 10 4

10 0

10 1

10 2

10 3

10 4

<F

L2-H

>: F

oxP

3 P

E 5

ul13.7

1.88

0.44 1.44

12.285.9

0

1

2

3

4

11.3

1.85

1.32 0.53

10.787.4

Figure 4.8

A comparison of CD25 high staining, CTLA-4 staining and GITR staining in a

tuberculosis infected individual at ex vivo – the correlation amongst these markers and

between these markers individually and FoxP3 was unreliable

GITR population CD25 population

CTLA population

FoxP3 expression

FoxP3 expression

FoxP3 expression

40

-10

010

20

3040

% C

D4+

T c

ells

exp

ress

ing

CD

25hi

0 10 20 30% CD4+ T cells expressing FoxP3

95% CI

R^2 = 0.05 Regression coefficient p<0.22

Regression - CD25hi on FoxP3

-10

01

02

03

040

% C

D4+

T c

ells

exp

ress

ing

CT

LA4

0 10 20 30% CD4+ T cells expressing FoxP3

95% CI

R^2 = 0.0005 Regression coefficient p<0.91

Regression - CTLA4 on FoxP3

-10

010

2030

% C

D4+

T c

ells

exp

ress

ing

GIT

R

0 10 20 30% CD4+ T cells expressing FoxP3

95% CI

R^2 = 0.042 Regression coefficient p<0.26

Regression - GITR on FoxP3

Figure 4. 9

Regression of CD25hi (a), CTLA-4 (b) and GITR (c) expression on FoxP3 failed to show

a statistically significant correlation with FoxP3 for any of the patient groups (p<0.22,

p<0.91, p<0.26 respectively)

REGRESSION CD25 ON FOXP3

REGRESSION CTLA-4 ON FOXP3

REGRESSION GITR ON FOXP3

(a)

(b)

(c)

41

4.4 CFSE staining

CFSE is an intracellular dye which binds DNA and is shared among daughter cells in a

predictable manner allowing for assessment of cell proliferation. It was utilised in this

study to assess the proliferative response of cells which expressed FoxP3 and CD4 to the

exogenous stimuli and to assess whether these cells are anergic in culture. As expected,

the positive control, anti-CD3, stimulated a strong proliferative response in CD4+ T cells

expressing FoxP3 and CD4+ T cells which did not express FoxP3 after 4 days in most

patients (Figure 4.10). The exception was the cohort of patients with HIV infection and

active TB who showed a significant decrease in frequencies of CD4+ T cells and no CD4+

T cell proliferation in response to anti-CD3. This was unexpected and suggested that

strong stimulation in this population group may have resulted either in anergy or in

apoptosis in this T cell subset. The possibility that this may have been a result of the

toxicity of the CFSE dye was excluded – there was no reduction in T cell frequency when

these cells were exposed to the dye in the absence of anti-CD3 stimulation. It was noted,

however, that the presence of the dye itself resulted in a significant loss of Tregs in both

the healthy controls and HIV infected individuals.

42

10 4

CD3+ CD4+06246 CFSE 100706 NO STIM.019Event Count: 10228

10 0 10 1 10 2 10 3 10 4

<FL1-H>: CFSE

10 0

10 1

10 2

10 3

10 4

<F

L2-H

>:

FO

XP

3 P

E 5

ul

0 0.039

98.41.58

4

CD3+ CD4+06246 CFSE 100706 ACD3.020Event Count: 17338

FSC-H: FSC-Height <FL1-H>: CFSE <FL4-H>: CD3 APC 5ul

10 0 10 1 10 2 10 3 10 4

<FL1-H>: CFSE

10 0

10 1

10 2

10 3

10 4

<FL2

-H>:

FO

XP

3 P

E 5

ul

3.36 2.34

38.456

Figure 4.10

CFSE dye dilution showing significant proliferation of CD3+ CD4+ FoxP3+ cells in

response to anti-CD3 stimulation

Proliferation of the non-Treg CD4+ T cells was also assessed to see whether there was a

response to stimuli. IFNγ secretion by CD4+ FoxP3- T cells and CD8+ T cells was also

measured and compared with proliferation.

As expected, there was a significant proliferative response in CD4 T cells in all

populations to anti-CD3 stimulation (except in co-infected subjects as discussed above)

CD3+ CD4+ T cells

CD3+ CD4+ T cells

FoxP3 expression

FoxP3 expression

Culture with no stimulation

Culture with anti-CD 3 stimulation

43

which correlated well with IFNγ production by both CD4 and CD8 T cells. There was no

significant difference in proliferative response to other stimuli, although individual

patients did show responses to PPD and tetanus, which correlated with their ability to

upregulate production of IFNγ. Gag and Nef produced weak proliferative responses and

expression of IFNγ with some exceptions in individual patients (Figure 4.12).

Interestingly, the proportion of FoxP3+ CD4+ CFSElow T cells correlated positively with

capability of CD4 cells to express IFN-γ and negatively with the ability of CD8 cells to

express IFN-γ when stimulated with Gag in uninfected individuals (Figure 4.12).

The ability of CD8 T cells to express IFN-γ correlated negatively with the frequency of

cells expressing FoxP3 in HIV infected individuals in response to anti-CD3 (p<0.03).

FoxP3 expression in CD4+ T cells correlated with the proliferative response of CD4+ T

cells to Nef in HIV infected individuals (Figure 4.13).

44

100 101 102 103 104

100

101

102

103

<F

L1-H

>: C

D4

FIT

C 2

0ul

0.6196.8

100 101 102 103 104

100

101

102

103

<F

L1-H

>: C

D4

FIT

C 2

0ul

2.42 0.22

24.872.6

10 0 10 1 10 2 10 3 10 4

10 0

10 1

10 2

10 3

10 4

<F

L1-H

>: C

D4

FIT

C 2

0ul

2.5 0.13

8.1589.2

100 101 102 103 104

<FL4-H>: IFN-g APC 5ul

100

101

102

103

<FL1

-H>:

CD

4 F

ITC

20u

l

2.58 0.099

4.5592.8

Figure 4.11:

Interferon- gamma expression at day 1 by CD4+ T cells in an individual with HIV and

active TB in response to no stimulation, anti-CD3, Gag superpool and Neg superpool

(CD4+ T cells on the y-axis and IFN-γ on x-axis). A significant response is shown to the

HIV specific peptides and to anti-CD3 by the non- CD4+ T cells (defined by their

expression of CD3)

Unstimulated population Anti-CD3 Stimulation

Nef Stimulation Gag Stimulation

IFNγ expression

IFNγ expression IFN-γ expression

IFN-γ expression

45

-1.5

-1-.

50

.51

% C

D4+

T c

ells

exp

ress

ing

INF

g w

ith G

ag s

timu

latio

n

-6 -4 -2 0 2% CD4+ T cells expressing FoxP3 with Gag stimulation

95% CI

R^2 = 0.843 Regression coefficient p<0.001

Uninfected groupRegression - INF gamma on FoxP3

Figure 4.12

A regression of change in FoxP3 on change in IFNγ expression in CD4+ T cells in

uninfected individuals with Gag stimulation showing a significant correlation (p<0.001)

-.3

-.2

-.1

0.1

.2%

CD

4+ C

SF

E lo

w T

cel

ls w

ith N

ef s

timul

atio

n

-4 -2 0 2% CD4+ T cells expressing FoxP3 with Nef stimulation

95% CI

R^2 = 0.802 Regression coefficient p<0.016

HIV infected groupRegression - CFSE measured proliferation on FoxP3

Figure 4.13

A linear regression of change in CFSE low on change in FoxP3 in CD4+ T cells in HIV

infected individuals showing a significant correlation between proliferation and Treg

frequencies with Nef stimulation after 4 days of culture (p<0.016)

LINEAR REGRESSION – IFNγ EXPRESSION ON FOXP3 EXPRESSION IN CD4+ T CELLS

LINEAR REGRESSION – CFSE MEASURED CD4+ T CELL PROLIFERATION ON FOXP3 IN HIV INFECTED INDIVIDUALS

Change in % CD4+ T cell expressing FoxP3 with Gag Stimulation 95 % CI R^2 = 0.843 Regression coefficient p<0.001

Ch

an

ge

in %

CD

4+

T ce

ll exp

ressin

g IF

Ng

with

Ga

g

Stim

ula

tion

Change in % CD4+ T cell expressing FoxP3 with Nef Stimulation 95 % CI R^2 = 0.802 Regression coefficient p<0.016

Ch

an

ge

in %

CD

4+

CF

SE

low

T ce

lls with

Ne

f Stim

ula

tio

n

46

5.0 Discussion

5.1 Ex vivo regulatory T cell frequencies are markedly lower in

patients with tuberculous disease than in normal controls and in

patients with HIV infection.

In contrast to recent findings suggesting that elevated Treg frequencies may be

responsible for the pathogenesis of symptomatic TB infection (Hougardy et al 2007,

Guyot-Revel et al 2006) , this study showed significantly reduced levels of Tregs as a

proportion of the CD3+ CD4+ T cells compared with uninfected controls. This may

suggest that symptomatic infection in the patient population under investigation may be

related to a failure to suppress an overactive immune response. Since the primary site of

infection of the tubercle bacillus is the macrophage, it is possible that suppression of the

immune response by the bacterium is counterproductive to its survival. Although Tregs

appear to be increased in frequency in HIV infected individuals, this effect is largely

ablated when these patients develop active TB disease. This ex vivo reduction in

frequency was maintained with culture in the patients with tuberculosis showing that the

proportion may be sustained with time. There was attrition in the frequencies of Tregs in

HIV infected individuals with culture compared with frequencies ex vivo. This effect has

been previously described although it is uncertain whether this represents effects of HIV

proteins or susceptibility of these cells to culture.

47

5.2 Regulatory T cells are not anergic in culture

It has previously been suggested that naturally occurring Tregs are anergic (Hori, 2004)

and that there is no response to stimulation in this population in the periphery. This is

important in patients who have lost a high number of CD4+ T cells as is the case in

advanced HIV infection because it suggests that a functional thymus will be required to

replenish the population. The stimulated Treg population (generated in the periphery)

must therefore consist predominantly of IL-10 or TGF-β secreting cells. This study

showed significantly higher frequencies of CD4+ T cells expressing FoxP3 with anti-CD3

stimulation. With CFSE dye dilution, it was clear that this represents in part proliferation

to this stimulus. In addition, there was significant proliferation of CD4+ T cells

expressing FoxP3 to tetanus in the uninfected control group.

5.3 Neither GITR nor CTLA4 are reliable markers for assessment of

Tregs

CTLA-4 (Cytotoxic T-lymphocyte associated protein 4) has been associated with Treg

populations (Ramsdell and Ziegler 2003, Thompson and Powrie 2004, Salomon et al

2000). This molecule is postulated to have a suppressive function accomplished by

binding to the B7 antigens on the antigen-presenting cells, thus ablating the co-

stimulatory pathways for T cell activation. Nevertheless, its function in the Treg

population still remains controversial as monoclonal antibodies directed against this

marker do not appear to impact the progression of autoimmune disease in mice (in this

case NOD mice or non-obese diabetic mice – Salomon et al 2000). In addition, it does not

48

appear to inhibit CD4+ CD25hi T cell suppressive function in humans’ in vivo or in vitro

culture, even though CTLA-4 polymorphisms have been associated with autoimmune

disorders in humans.

Glucocorticoid-induced tumour-necrosis factor receptor-related protein or GITR has been

linked to the regulatory activities of Tregs (Hisaeda et al 2005, Cardona et al 2006). A

transfer of T cells, which are depleted for GITR, into mice lacking a thymus results in

more aggressive autoimmunity than if only CD25 depleted T cells are transferred into

these mice (Uraushihara et al 2003)

In this study, CTLA-4 and GITR were correlated with FoxP3 and CD25high expression.

Both FoxP3 and CD25 have been used to define the regulatory population in mice and

humans, but certain authors have suggested that FoxP3 may be upregulated in response to

activation (Morgan et al 2005). An attempt was made to characterise these 2 markers,

with established regulatory functions, on the cell populations in this study to attempt to

establish a regulatory phenotype in the absence of depletion studies. Neither of these

markers correlated consistently with FoxP3 expression in this study and could thus not be

considered useful as a surrogate marker of this population. In this study, both molecules

were assessed by flow cytometric analysis following the manufacturer’s instructions for

the monoclonal antibody staining. Because CTLA-4 and FoxP3 were assessed by

intracellular staining, compensation was suboptimal and the data regarding this marker

were treated with reserve. It is possible that it would be preferable to assess these

molecules by quantitative reverse transcriptase PCR.

49

Other molecules are currently being explored as surface markers for Tregs. Tregs express

the other 2 chains of the IL2 receptor, CD122 (IL2-R beta chain) and CD132 (IL2-R

gamma chain). In addition they express the intercellular adhesion molecule, LFA3 or

CD58. Recent studies have also demonstrated that downregulation of the IL-7α chain

(CD127) may have utility in characterizing this population (Hartigan-O’Connor et al

2007).

5.4 Tregs can respond to specific stimuli

In HIV infected individuals, stimulation with an HIV specific peptide resulted in an

increase in the frequency of FoxP3-expressing cells as a proportion of CD3+ CD4+ T cells.

This may represent apoptosis in the non-Treg population rather than active proliferation

of the Gag specific Tregs. Gag specific proliferation was not significantly different in the

HIV infected population compared with either unstimulated cells or with uninfected

individuals. It is also interesting to note that IFN-γ production in CD4 cells in uninfected

individuals stimulated with Gag correlated strongly with the frequency of cells ex vivo in

individuals with active TB disease compared with uninfected controls, no similar

response was noted in response to stimulation with PPD, which contains mycobacterial

antigens. It must be noted that the concentration of PPD was suboptimal and that at

higher concentrations, a response might have been noted.

50

5.5 CD4+ T cell proliferation correlates with interferon-gamma

production in CD4+ T cells

As expected, there was a significant correlation between CD4+ proliferation and IFNγ

production by CD4+ T cells in response to all stimuli in uninfected controls. A significant

correlation was not present in individuals with active TB for any stimulation apart from

with PPD. The response to HIV specific peptides within HIV infected individuals with

and without active TB was broadly divergent from patient to patient. This probably

suggests that there is no clear uniform pattern and that a larger sample size will be needed

for greater clarification of the response.

5.6 HIV specific peptides exert an immunomodulatory role in Tregs

with prolonged exposure

The frequency of CD4+ T cells expressing FoxP3 in uninfected controls correlated

positively with the response of these cells by IFNγ secretion at day 1 in response to Gag

stimulation . In conjunction with the response of cells from an HIV infected individual to

Gag at day 4, this suggests that this peptide may have a function in selecting out CD4+ T

cells which respond to this HIV peptide.

There was a highly significant correlation between FoxP3 expression after 4 days of

culture and CD4 T cell proliferation in HIV patients in response to Nef stimulation. There

was no significant proliferation of FoxP3 positive cells or increase in the proportion of

cells which expressed FoxP3 in these individuals although it must also be noted that there

51

was a trend for Nef to reduce FoxP3 expression in uninfected controls. These data

suggest that Nef may not influence FoxP3 expression directly as an immunosuppressive

strategy although Nef stimulation also resulted in a significant negative correlation

between IFNγ secretion by CD8+ T cells and the frequency of FoxP3 cells in uninfected

controls. Some of the previously described immunological effects of Nef expression

include CD4 molecule down-regulation and impaired thymocyte proliferation in vivo

(Pennington et al 1997) and MHC class I and II down-regulation (Schindler et al, 2007;

Noviello et al 2007) which are all associated with an abnormal immunological synapse

formation. Polymorphisms in the Nef gene have been associated with differential

progression of HIV infection to AIDS (Walker et al 2007). These results were obtained

with a Nef peptide pool, rather than a complete Nef protein and it is unclear what effects

would be obtained with the full protein structure.

52

6.0 Conclusion

Tregs have been described as a population of cells which regulate the adaptive immune

response. Clearly, these cells will be of vital importance in diseases which affect the

immune system as profoundly as HIV and tuberculosis. This study contains preliminary

work using flow cytometric assays to assess the frequency of these cells in patients

affected with these two diseases and attempts to answer further questions regarding the

behaviour of this population in culture and under conditions of stimulation.

The data are subject to some important limitations. A small sample was investigated and

thus generalization of these results to the patient population as a whole not feasible and

requires confirmation in a larger study. In addition, controversy exists as to whether

FoxP3 is the best marker to characterise human regulatory T cells. Certain studies

(Morgan et al 2005, Allan et al 2007) suggest that effector T cells may upregulate FoxP3

transiently in response to activation. It is unclear whether the increased frequency of

FoxP3-expressing cells in HIV-infected patients in this study represent T cells which are

subject to chronic activation. Depletion studies using CD25hi to isolate regulatory T cells,

followed by co-culture with CD25lo cells would have been useful to confirm that the cells

expressing FoxP3 in this study had regulatory properties. The data does, nevertheless,

support the findings of other groups that the Treg population is upregulated in HIV

infected individuals. As the data regarding the role of Tregs in tuberculosis are more

controversial, the meaning of the reduced frequency of FoxP3 expressing cells in this

population of patients is uncertain. The data do show conclusively, however, that this

53

population is not anergic in vitro and this may indicate that FoxP3 expressing Tregs can

be induced by specific stimuli in vivo.

Studies of proliferation of antigen-specific T cells and IFNγ production were performed

to assess the function of FoxP3 expressing cells on other cells in culture – it has been

suggested that FoxP3 may be an activation marker (Morgan et al 2005). These did not

show consistent results although some observations including the significant negative

correlation between FoxP3 expression and IFNγ production by CD8+ T cells in response

to Nef stimulation suggest that there may have been a direct suppressive function from

this population. Future studies using co-cultures of Tregs and antigen-specific cells from

HIV infected individuals and individuals with active tuberculosis may be of value,

particularly if it can be shown that Tregs can be isolated and cultured. These data

question whether bright CD25 expression is a good surrogate marker for FoxP3 and it is

still unclear how these cells would best be separated in a viable state. The data showing

the correlation of CD4 proliferation after 4 days of culture with stimulation with Nef and

the frequency of FoxP3 positive cells at this time point is interesting and the role of Nef

in this population may be worth exploring further.

Future directions include mapping the pathways of the stimulants, use of other techniques

to demonstrate the upregulation of FoxP3 in the population (in particular, reverse-

transcription PCR) and exploration of other markers of this population. In addition, a

longitudinal study to assess whether FoxP3 expression correlates with clinical outcome

54

may be of use in individuals with active tuberculosis or HIV infection. It is possible that

Treg frequency may be an important clinical marker of progression or response to

therapy but this will still need to be determined.

55

APPENDIX

Statistical results for experimental data

Table 4.1:

Treg frequencies following stimulation compared with unstimulated cells at day 4 in all

four classes (ND= no statistical difference, I=increased compared with control,

D=decreased compared with controls)

Uninfected controls

TB diseased

subjects HIV infected subjects

Co-infected

subjects

Anti-CD3 (0.1ug/ml) I (p<0.011) I (p<0.006) I (p<0.001) ND (p<0.148)

PPD (0.01ug/ml) ND (p<0.138) ND (p<0.154) ND (p<0.123) ND (p<0.194)

Tetanus toxoid (2 ug/ml) ND (p<0.071) ND (p<0.125) ND (p<0.051) ND (p<0.304)

Gag superpool (2ug/ml) ND (p< 0.497) ND (p<0.367) I (p<0.05) ND (p<0.406)

Nef superpool (2ug/ml) ND (p<0.065) ND (p<0.422) ND (p<0.341) ND (p<0.340)

56

Table 4.2

CFSE measured proliferation of Tregs to stimulation compared with no stimulation on

day 4 (ND=no statistical difference, I=increased, D=decreased)

Uninfected controls

TB diseased

subjects

HIV infected

subjects

Co-infected

subjects

Anti-CD3 (0.1ug/ml) I (p<0.020) I (p<0.008) I (p<0.002) D(p<0.05)

PPD (0.01ug/ml) ND (p<0.194) ND (p<0.184) ND (p<0.098) ND (p<0.278)

Tetanus toxoid (2 ug/ml) ND (p<0.372) ND (p<0.474) ND (p<0.258) ND (p<0.427)

Gag superpool (2ug/ml) ND (p<0.310) ND (p<0.269) ND (p<0.356) ND (p<0.400)

Nef superpool (2ug/ml) ND (p<0.215) ND (p<0.269) ND (p<0.404) ND (p<0.384)

Table 4.3

Comparison of CFSE measured regulatory T cell proliferation in TB, HIV and coinfected

subjects compared with uninfected controls (ND=no statistical difference, S=suppressed

with respect to controls, I=increased with respect to controls

TB diseased subjects HIV infected subjects Co-infected subjects

Unstimulated ND (p<0.261) ND (p<0.156) ND (p<0.352)

Anti-CD3 (0.1ug/ml) ND (p<0.325) ND (p<0.105) S (p<0.012)

PPD (0.01ug/ml) ND (p<0.283) ND (p<0.234) ND (p<0.366)

Tetanus toxoid (2 ug/ml) ND (p<0.357) S (p<0.031) ND (p<0.354)

Gag superpool (2ug/ml) ND (p<0.232) ND (p<0.251) ND (p<0.372)

Nef superpool (2ug/ml) ND (p<0.358) ND (p<0.430) ND (p<0.256)

57

Table 4.4

Correlation between CD4+T cell proliferation and gamma interferon expression by

CD4+T cells

Uninfected

controls

HIV infected

subjects

TB diseased

subjects

Coinfected

subjects

Anti-CD3

Correlation

coefficient=0.767,

(p<0.047)

Correlation

coefficient=0.451,

(p<0.671)

Correlation

coefficient=-0.906,

p<0.622

Correlation

coefficient=-0.108,

(p<0.9987)

PPD

Correlation

coefficient=0.960,

(p<0.000)

Correlation

coefficient=0.678,

(p<0.094)

Correlation

coefficient=-0.999,

(p<0.035)

Correlation

coefficient=-0.989,

(p<0.031)

Tetanus toxoid

Correlation

coefficient=0.929,

(p<0.003)

Correlation

coefficient=0.631,

(p<0.448)

Correlation

coefficient=-0.136,

p<0.999

Correlation

coefficient=-0.220,

(p<0.997)

Gag

Correlation

coefficient=0.892,

(p<0.042)

Correlation

coefficient=0.213,

(p<0.956)

Correlation

coefficient=0.650,

(p<0.909)

Correlation

coefficient=0.621,

(p<0.761)

Nef

Correlation

coefficient=0.965,

(p<0.001)

Correlation

coefficient=0.405,

(p<0.746)

Correlation

coefficient=0.993,

(p<0.07)

Correlation

coefficient=0.734,

(p<0.605)

58

Table 4.5

Proliferation of FoxP3+ CD4+ T cells correlated with interferon γ production by CD8+ T

cells

Uninfected controls HIV infected subjects

TB infected

subjects Coinfected subjects

Anti-CD3

Correlation

coefficient=0.544,

(p<0.342)

Correlation

coefficient=-0.854,

(p<0.030)

Correlation

coefficient=-0.970,

(p<0.365)

Correlation

coefficient=-0.982,

(p<0.094)

PPD c=-0.178, p<0.956 c=-0.022, p<1.00 c=-0.985, p<0.460 c=-1, p<0.017

Tetanus c=0.284, p<0.874 c=-0.032, p<1.00 c=-0.414, p<0.980 c=-1, p<0.09

Gag c=-0.323, p<0.934 c=-0.393, p<0.825 c=0.972, p<0.386 c=-0.906, p<0.623

Nef c=-0.881, p<0.026 c=-0.484, p<0.700 c=-0.403, p<0.982 c=-0.403, p<0.982

59

Table 4.6

FoxP3 frequency correlated against CFSE measured proliferation and secretion of

interferon gamma by CD4+ T cells

Uninfected controls

HIV infected

individuals

TB infected

individuals Coinfected individuals

Anti-CD3 (2ug/ml)

FoxP3 frequency

compared with CD4

proliferation

Correlation

coefficient t=0.68,

(p<0.872)

Correlation coefficient

=252, p<0.995

Correlation

coefficient=-0.895,

(p<0.357)

Correlation coefficient=

-0.744, p<0.852

FoxP3 frequency

compared with Interferon

secretion

Correlation

coefficient =-0.259,

(p<0.1128)

Correlation coefficient

=0.252, (p<0.995)

Correlation coefficient

=-0.969, (p<0.404)

Correlation coefficient=-

0.529, p<0.852

PPD (0.01ug/ml)

FoxP3 frequency

compared with CD4

proliferation

Correlation

coefficient= 0.400,

(p<0.615)

Correlation

coefficient = 0.021,

(p=1)

Correlation

coefficient =-0.972,

(p<0.387)

Correlation coefficient

=-0.760, (p<0.834)

FoxP3 frequency

compared with Interferon

secretion

Correlation

coefficient =0.5,

(p<0.444)

Correlation

coefficient=0.021,

(p=1)

Correlation

coefficient =-0.185,

( p<0.998)

Correlation

coefficient=-0.784,

(p<0.519)

Tetanus toxoid (2ug/ml)

FoxP3 frequency

compared with CD4

proliferation

Correlation

coefficient =0.605,

(p<0.232)

Correlation

coefficient=0.500,

(p<0.671)

Correlation

coefficient=0.757,

(p<0.838)

Correlation coefficient

=0.124, (p<1)

FoxP3 frequency

compared with Interferon

secretion

Correlation

coefficient=0.59,

(p<0.260)

Correlation

coefficient =0.149,

(p<0.984)

Correlation

coefficient=0.537,

(p<0.988)

Correlation

coefficient=0.231,

(p<0.988)

Gag superpool (2ug/ml)

60

FoxP3 frequency

compared with CD4

proliferation

Correlation

coefficient=0.576,

(p<0.298)

Correlation

coefficient=-0.256,

(p<0.947)

Correlation

coefficient=0.791,

(p<0.804)

Correlation

coefficient=-0.731,

(p<0.858)

FoxP3 frequency

compared with Interferon

secretion

Correlation

coefficient=0.921,

(p<0.001)

Correlation

coefficient=-0.173,

(p<0.98)

Correlation

coefficient=-0.186,

(p<0.99)

Correlation

coefficient=0.806,

(p<0.476)

Nef superpool (2ug/ml)

FoxP3 frequency

compared with CD4

proliferation

Correlation

coefficient=0.364,

(p<0.707)

Correlation

coefficient=0.896,

(p<0.046)

Correlation

coefficient=-0.473,

(p<0.969)

Correlation

coefficient=0.863,

(p<0.709)

FoxP3 frequency

compared with Interferon

secretion

Correlation

coefficient=0.421,

(p<0.594)

Correlation

coefficient =-0.274,

(p<0.910)

Correlation

coefficient=-0.981,

(p<0.329)

Correlation

coefficient=-0.151,

(p<0.997)

61

REFERENCES

ONLINE REFERENCES

www.who.int/mediacentre/factsheets

www.unaids.org

http://www.bdbiosciences.com/pharmingen/protocols/Intracellular_Cytokine

1. Ahmadzadeh, M and Rosenberg S. Il-2 administration increases CD4+CD25hiFoxP3+ regulatory T

cells in cancer patients. Blood. 2006 Mar 15;107(6):2409-14

2. Allan SE, Crome SQ, Crellin NK, Passerinin L, Steiner TS, Bacchetta R, Roncarolo MG and Levings

MK. Activation-induced FOXP3 in human T effector cells does not suppress proliferation or cytokine

production. International Immunology 2007 Apr; 19 (4): 345-54

3. Baccheta, R, Gregori, S and Roncarolo, M. CD4+ regulatory T cells: Mechanisms of induction and

effector function. Autoimmunity reviews 4:8 (2005) 491-496

4. Baecher-Allan, C, Wolf, E and Hafler, D. Functional analysis of highly defined FACS-isolated

populations of human regulatory CD4+ CD25+ T cells. Clinical immunology 115:1 (2005) 10-18

5. Baecher-Allan, Viglietta, V and Hafler, D. Human CD4+CD25+ regulatory T cells Seminars in

Immunology 16:2 (2004) 89-9

6. Bendelac, A, Savage, P and Teyton, L The biology of NKT Cells. Annual Reviews in Immunology

(2007)

7. Beyersdorf, N, Hanke, T, Kerkau, T and Hunig, T. CD28 superagonists but a break on autoimmunity

by preferentially activating CD4+CD25+ regulatory T cells. Autoimmunity Reviews 5:1 (2006) 40-45

8. Bluestone, J and Tang, Q. How do CD4+CD25+ regulatory T cells control autoimmunity.Current

opinion in immunology 17:6 (2005) 638-642

9. Bosco N, Hung H, Pasqual N, Jouvin-Marcdhe E, Marche P, Gascoigne N and Ceredig R. Role of the T

cell receptor alpha chain in the development and phenotype of naturally arising CD4+CD25+ T cells

Molecular immunology 43:3 (2006) 246-254

62

10. Bynoe MS and Viret C. Foxp3+CD4+ T cell-mediated immunosuppression involves extracellular

nucleotide catabolism Trends in Immunology (2008) Mar; 29(3) 199-102

11. Cardona, I, Goleva, E, Ou, L and Leung, D. Staphylococcal enterotoxin B inhibits regulatory T cells by

inducing glucocorticoid-induced TNG receptor-related protein ligand on monocytes Journal of Allergy

and Clinical Immunology (2006) Mar;117(3):688-95.

12. Chan, J and Flynn, J. The immunological aspects of latency in Tuberculosis Clinical Immunology

(2004) 110 2-12

13. Chase AJ, Sedaghat AR, German JR, Gama L, Zink MC, Clements JE, Siliciano RF. Severe depletion

of CD4+ CD25+ regulatory T cells from the intestinal lamina propria but not peripheral blood or

lymph nodes during acute simian immunodeficiency virus infection. Journal of Virology. (2007)

Dec;81(23):12748-57.

14. Chatila, T. Role of regulatory T cells in human diseases. Journal of allergy and clinical Immunology

(2005) 116:5 949-959

15. Chen S, Ishii N, Ine S, Ikedam S, Fujimura T, Ndhlovu L, Soroosh P, Tada K, Harigae H, Kameoka, J,

Kasai N, Sasaki T and Sugamura K. Regulatory T cell-like activity of FoxP3+ adult T cell leukaemia

cells. International Immunology (2006) Feb;18(2):269-77.

16. Chen X, Zhou B, Li M, Deng Q, Wu X, Le X, Wu C, Larmonier N, Zhang W, Zhang H, Wang H,

Katsanis E. CD4(+)CD25(+)FoxP3(+) regulatory T cells suppress Mycobacterium tuberculosis

immunity in patients with active disease. Clinical Immunology. (2007) Apr;123(1):50-9. 17

17. Chen, Z, Herman, A, Matos, M, Mathis, D and Benoist, C. Where CD4+CD25+ Treg cells impinge on

autoimmune diabetes. Journal of Experimental Medicine (2005) 21:202 1387-1397

18. Cooper AM, Dalton DK, Stewart TA, Griffen JP, Russell DG, Orme IM. Disseminated tuberculosis in

IFN-γ gene-disrupted mice.. Journal of Experimental medicine (1993). 178: 2243–47

19. Cooper AM, Magram J, Ferrante J, Orme IM.. Interleukin 12 (IL-12) is crucial to the development of

protective immunity in mice intravenously infected with Mycobacterium tuberculosis. Journal of

Experimental Medicine (1997). 186:39–45

20. Cortesini, R and Suciu-Foca, N. The concept of “partial” clinical tolerance. Transplant Immunology

(2004) 13:2 101-104

63

21. Crellin N, Garcia R, Hadisfar O, Allan S, Stenier T and Levings M. Human CD4+ T cells express

TLR5 and its Ligand Flagellin enhances the Suppressive Capacity and Expression of FoxP3 in

CD4+CD25+ T regulatory cells. Journal of Immunology (2005) 175 8051-8059

22. Duplan V, Beriou G, Heslan J, Bruand C, Dutartre P, Mars L, Liblau R, Cuturi M and Saoudi A. LF15-

0195 treatment protects against central nervous system autoimmunity by favoring the development of

FoxP3-expressing regulatory CD4 T cells. Journal of immunology (2006) 15:176 839-847

23. Eggena MP, Barugahare B, Jones N, Okello M, Mutalya S, Kityo C, Mugyenyi P, Cao H. Depletion of

regulatory T cells in HIV infection is associated with immune activation Journal of Immunology (2005)

Apr 1; 174 (7): 4407-14

24. Fan Y, Yang B and Wu C Phenotypically and functionally distinct subsets of natural killer cells in

human PBMCs Cell Biology International (2008) Feb;32(2):188-97.

25. Fantini, M, Becker, C, Monteleone, G, Pallone, F, Galle, P and Neurath, M. Cutting edge: TGF-β

induces a regulatory phenotype in CD4+ CD25- T cells through FoxP3 induction and downregulation

of Smad7. Journal of Immunology 172 (2004) 5149-5153

26. Flynn JL, Chan J, Triebold KJ, Dalton DK, Stewart TA, Bloom BR. 1993. An essential role for

interferon-γ in resistance to Mycobacterium tuberculosis infection. Journal of Experimental Medicine

178:2249–54

27. Fujisima, M, Hirokawa, Fujisima, N and Sawada, K. TCRαβ repertoire diversity of human naturally

occurring CD4+CD25+ regulatory T cells. Immunology Letters (2005) 99:2 193-197

28. Gartner, D, Hoff, H, Gimsa, U, Burmester, G, Brunner-Weinzierl, M. CD25 regulatory T cells

determine secondary but not primary remission in EAE: Impact on long-term disease progression.

Journal of Neuroimmunology (2006) Mar;172(1-2):73-84

29. Gavin, M and Rudensky, A. Control of immune homeostasis by naturally arising regulatory CD4+ T

cells Current opinion in Immunology 15:6 (2003) 690-696

30. Goleva, E, Cardona, I, Ou, L and Leung, D. Factors that regulate naturally occurring T regulatory

cell-mediated suppression. Journal of Allergy and Clinical Immunology 116:5 (2005) 1094-1100

64

31. Gondek DC, Lu LF, Quezada SA, Sakaguchi S, Noelle RJ.Cutting edge: contact-mediated suppression

by CD4+CD25+ regulatory cells involves a granzyme B-dependent, perforin-independent

mechanism.Journal of Immunology (2005) Feb 15;174(4):1783-6.

32. Good, M. Identification of Early Cellular immune factors regulating growth of malaria parasites in

humans. Immunity (2005) 23:3 241-242

33. Gordon, S. Pattern Recognition receptors. Doubling up for the innate immune response Cell (2002)

111:7 927-930

34. Graca, L, Chen, T, Le Moine, A, Cobbold, S, Howie, D and Waldmann, H. Dominant

tolerance :activation thresholds for peripheral generation of regulatory T cells. Trends in Immunology

26:3 (2005) 130-135

35. Grossman W, Verbsky J, Barchet W, Colonna M, Atkinson J and Ley T. Human T regulatory cells can

use the perforin pathway to cause autologous target cell death. Immunity 21:4 (2004) 589-601

36. Gruenberg J and Stenmark H: The biogenesis of multivesicular endosomes. Nature Reviews Molecular

Cell Biology (2004) 5:317-323.

37. Guyot-Revol, V, Innes, J, Hackforth, S, Hinks, T and Lalvani, A. Regulatory T cells are expanded in

blood and disease sites in Tuberculosis patients. American Journal of Respiratory Critical Care

Medicine 2006 Apr 1;173(7):803-10.

38. Hartigan-O'Connor DJ, Poon C, Sinclair E, McCune JM. Human CD4+ regulatory T cells express

lower levels of the IL-7 receptor alpha chain (CD127), allowing consistent identification and sorting of

live cells. Journal of Immunological Methods. (2007) Jan 30;319(1-2):41-52.

39. Hisaeda H, Hamano S, Mitoma-Obata C, Tetsutani K, Imai T, Waldmann H, Himeno K and Yasutomo

K. Resistance of regulatory T cells to glucocorticoid-inducted TNFR family-related protein (GITR)

during Plasmodium yoelli infection. European Journal of Immunology (2005) 35:12 3516 - 3524

40. Hoffmann, P and Edinger, M. CD4+CD25+ regulatory T cells and Graft-versus-host disease.

Seminars in haematology (2006) 43:1 62-69

41. Hori, S and Sakaguchi, S. FoxP3: a critical regulator of the development and function of regulatory T

cells. Microbes and Infection (2004) 6:8 745-751

65

42. Hori, S, Nomura, T and Sakaguchi, S. Control of regulatory T cell development by the transcription

factor FoxP3. Science (2003) 299:5609 1057-1061

43. Houben E, Nguyen L and Pieters J. Interaction of pathogenic mycobacteria with the host immune

system. Current Opinion in Microbiology (2006), 9:76–85

44. Hougardy JM, Place S, Hildebrand M, Drowart A, Debrie AS, Locht C, Mascart F. Regulatory T cells

depress immune responses to protective antigens in active tuberculosis.

American Journal of Respiratory Critical Care Medicine (2007) Aug 15;176(4):409-16.

45. Houyen EN, Nguyen L, Pieters J Interaction of pathogenic mycobacteria with the host immune system.

Current Opinion in Microbiology (2006) Feb; 9 (1); 76-85

46. Hsieh, C, Liang, Y, Tyznik, A, Self, S, Liggitt, D and Rudensky, A. Recognition of the peripheral self

by naturally arising CD25+ CD4+ T cell receptors. Immunity (2004) 21:2 267-277

47. Huehn, J and Hamann, A. Homing to suppress: address codes for Treg migration. Trends in

Immunology (2004) 25:12 632-636

48. Ikezawa, Y, Nakazawa, M, Tamura, C, Takahashi, K, Minami, M and Ikezawa, Z. Cyclophosphamide

decreases the number, percentage and the function of CD25+ CD4+ regulatory T cells, which

suppress induction of contact hypersensitivity. Journal of Dermatological Sciences 39:2 (2005) 105 –

112

49. Jasmer, RM, Nahid P and Hopewell PC. Latent Tuberculosis Infection New England Journal of

Medicine (2002) Dec; 347 1860

50. Karagiannidis C, Akdis M, Holopainen P, Woolley N, Hense G, Ruckert B, Mantel P, Menz G, Akdis

C, Blaser K and Schmidt-Weber C. Glucocorticoids upregulate FoxP3 expression and regulatory T

cells in asthma. Journal of Allergy and Clinical Immunology (2004) 114:6 1425-1433

51. Kasprowicz D, Smallwood S, Tyznik A and Ziegler S. Scurfin (FoxP3) controls T-dependent immune

response in vivo through regulation of CD4+ T cell effector function. Journal of Immunology (2003)

171 1216-1223

52. Kasprowicz, D, Droin, N, Soper, D, Ramsdell, F, Green, D and Ziegler, S. Dynamic regulation of

FoxP3 expression controls the balance between CD4+ T cell activation and cell death. European

Journal of Immunology (2005) 35:12 3424 - 3432

66

53. Kauffman, S Recent findings in immunology give tuberculosis vaccines a new boost Trends in

Immunology (2005) Dec; 26(12): 660-7

54. Kaufmann S Tuberculosis: Back on the Immunologists’ Agenda Annual. Reviews. In Immunology

(2004) 22:599–623

55. Kelsen J, Angholt J, Hoffman H, Romer J, Hvas C and Dahlerup J. FoxP3+CD4+CD25+ T cells with

regulatory properties can be cultured from colonic mucosa of patients with Crohn’s disease. Clinical

and Experimental Immunology (2005) 141 549-557

56. Khazaie, K and von Boehmer, H. The impact of CD4+ CD25+ Treg on tumor specific CD8+ T cell

cytotoxicity and cancer. Seminars in cancer biology (2006)16:2 124-136

57. Kronenberg M and Havran W. Frontline T cells: gammadelta T cells and intraepithelial lymphocyte.

Immunology Reviews (2007) Feb 215:5-7

58. Kursar M, Koch M, Mittrücker HW, Nouailles G, Bonhagen K, Kamradt T, Kaufmann SH.Cutting

Edge: Regulatory T cells prevent efficient clearance of Mycobacterium tuberculosis.Journal of

Immunology (2007) Mar 1;178(5):2661-5.

59. Lanzavecchia, A and Sallusto, F. Understanding the generation and function of memory T cell subsets.

Current opinion in Immunology (2005) 17:3 326-332

60. LeY, Yu X, Ruan L, Wang Qi D, Lu X, Kong Y, Cai K, Pang S, Shi X and Wang J. The

immunopharmacological properties of transforming growth factor beta. International

Immunopharmacology. (2005) 5:13-14 1771-1782

61. Lim H, Hillsamer P, Banham A and Kim C.H. Cutting edge: direct suppression of B cells by CD4+

CD25+ regulatory T cells. Journal of Immunology (2005) Oct 1;175 (7) 4180-3

62. Lopez M, Aguilera R Perez X, Mendoza-Naranjo A, Pereda C, Ramirez M, Ferrada C, Aguillon J and

Salazar-Onfray F. The role of regulatory T lymphocytes in the induced immune response mediated by

biological vaccines. Immunobiology (2006) 211(1-2):127-36.

63. Maerten, P, Kwon, B, Shen, C, De Hertogh, G, Cadot, P, Bullens, D, Overbergh, L, Mathieu, C, Van

Assche, G, Geboes, K, Rutgeerts, P and Ceuppens, J. Involvement of 4-1BB (CD137)-4-1Bbligand

interaction in the modulation of CD4+ T cell-mediated inflammatory colitis. Clinical and Experimental

Immunology 143 (2005) 228-236

67

64. Maggi, E, Cosmi, L, Liotta, F, Romagnani, S and Annunziato, F. Thymic regulatory T cells.

Autoimmunity Reviews (2005) 4:8 579-586

65. Maker, A, Attia, P and Rosenberg, S. Analysis of the cellular mechanism of antitumour responses and

autoimmunity in patients treated with CTLA-4 blockade. Journal of Immunology 1:175 (2005) 7746-

7754

66. Morgan M, Van Bilesen J, Bakker A, Heemskerk B, Schilham M, Hartgers F, Elfrink B, Van der

Zanden L, De Vries R, Huizinga T, Ottenhoff T and Toes R. Expression of FoxP3 mRNA is not

confined to CD4+25+ T regulatory cells in humans. Human Immunology (2005) 66:1 13-20

67. Morgan ME, van Bilsen JH, Bakker AM, Heemskerk B, Schilham MW, Hartgers FC, Elferink BG, van

der Zanden L, de Vries RR, Huizinga TW, Ottenhoff TH, Toes RE. Expression of FoxP3 mRNA is not

confined to CD4+ CD25 T regulatory cells in humans. Human immunology (2005) Jan: 66(1): 13-20

68. Nixon D, Aandahl E and Michaelsson J. CD4+CD25+ regulatory T cells in HIV infection. Microbes

and Infection 7:7-8 (2005) 1063-1065.

69. North, R.J. and Jung, Y Immunity to tuberculosis Trends in Immunology (2005) Dec 26:12

70. Noviello CM, Pond SL, Lewis MJ, Richman DD, Pillai SK, Yang OO, Little SJ, Smith DM, Guatelli

JC. Maintenance of Nef-mediated modulation of major histocompatibility complex class I and CD4

after sexual transmission of human immunodeficiency virus type 1: Journal of Virology (2007)

May;81(9):4776-86.

71. O’Garra, A. Development and function of IL-10-secreting regulatory T cells: Comparison with

naturally occurring CD4+CD25+ regulatory T cells. International Congress Series (The Innate

System: Strategies for Disease Control. Proceedings of the Uehara Memorial Foundation Symposium

on the Innate Immune System: Strategies for Disease Control, Tokyo) 1285 (2005) 160-168

72. Oswald-Richter K, Grill SM, Shariat N, Leelawong M, Sundrud MS, Haas DW, Unutmaz D. HIV

infection of naturally occurring and genetically reprogrammed human regulatory T-cells.PLoS Biol.

(2004)Jul;2(7):E198.

73. Pennington DJ, Jenkins SA, Brady HJ, Miles CG, Dzierzak EA, Abraham DJ. HIV- I Nef severely

impairs thymocyte development and peripheral T-cell function by a CD4-independent

mechanism.Genes and Function. (1997) Dec;1(5-6):321-35

68

74. Perrone G, Ruffini PA, Catalano V, Spino C, Santini D, Muretto P, Spoto C, Zingaretti C, Sisti V,

Alessandroni P, Giordani P, Cicetti A, D'Emidio S, Morini S, Ruzzo A, Magnani M, Tonini G, Rabitti

C, Graziano F. Intratumoural FOXP3-positive regulatory T cells are associated with adverse

prognosis in radically resected gastric cancer Eur J Cancer. (2008) Sep;44(13):1875-82.

75. Pillai, V, Baughman, E and Karandikar F.22. Suppressive Property of Activated FOXP3+ T Cells

Revealed by a Novel Suppression Assay Clinical Immunology, Volume 127, Supplement 1, 2008, Page

S50

76. Ramsdell, F and Ziegler, S. Transcription factors in autoimmunity. Current opinion in Immunology

(2003) 15:6 718-724

77. Rieger K, Loddenkemper C, Maul J, Fietz T, Wolff D, Terpe H, Stenier B, Berg E, Miehlke S,

Bornhauser M, Schneider T, Zeitz M, Stein H, Duchmann T and Uharek L. Mucosal FoxP3 regulatory

T cells are numerically deficient in acute and chronic GvHD. Blood 2006 Feb 15;107(4):1717-23.

78. Roberts T, Beyers N, Aguirre A, Walzl G. Immunosuppression during active tuberculosis is

characterized by decreased interferon- gamma production and CD25 expression with elevated

forkhead box P3, transforming growth factor- beta , and interleukin-4 mRNA levels.Journal of

Infectious Disease (2007) Mar 15;195(6):870-8.

79. Romagnani, S. Introduction: characterisation and functions of human T regulatory cells. Microbes and

Infection (2005) 7:7-8 1015-1016

80. Sakaguchi, S. Regulatory T cells: Key controllers of Immunologic Self-tolerance. Cell (2000) 101:5

455-458

81. Salomon, B, Lenschow, D, Rhee, L, Ashourian, N, Singh, B, Sharpe, A and Bluestone, J. B7/CD28

Costimulation is essential for the homeostasis of the CD4+CD25+ immunoregulatory T cells that

control Autoimmune diabetes. Immunity (2000) 12:4 431-440

82. Sato K, Tateishi S, Kubo K, Mimura T, Yamamoto K and Kanda H. Downregulation of IL-12 and a

novel negative feedback system mediated by CD25+CD4+ T cells. Biochemical and Biophysical

Research Communications (2005) 220:1 226-232

69

83. Schindler M, Wildum S, Casartelli N, Doria M, Kirchhoff F Nef alleles from children with non-

progressive HIV-1 infection modulate MHC-II expression more efficiently than those from rapid

progressors. AIDS (2007) May 31;21(9):1103-7.

84. Scott-Browne JP, Shafiani, S, Tucker-Heard G, Ishida-Tsubota K, Fontenot JD, Rudensky A, Bevan

MJ, Urdahl, K Expansion and function of Foxp3-expressing T regulatory cells during tuberculosis.

Journal of Experimental Medicine (2007) Sep 3; 204(9): 2159-69

85. Serra P, Amrani A, Yamanouchi J, Han B, Thiessen S, Utsugi T, Verdaguer J and Santamaria P. CD40

ligation releases immature dendritic cells from the control of regulatory CD4+CD25+ T cells.

Immunity (2003) 19:6 877-889

86. Shapiro S and Wilk M An analysis of variance test for normality(complete samples) Biometrika (1965)

52:591-611

87. Stenger, S and Modlin, R. Control of Mycobacterium tuberculosis through mammalian Toll-like

receptors Current opinion in immunology (2002) 14: 452-457

88. Taams, L, Van Amelsfort, J, Tiemessen, M, Jacobs, K, De Jong, E, Akbar, A, Bijlsma, J and Lafeber,

F. Modulation of monocyte/macrophage function human CD4+CD25+ regulatory T cells. Human

Immunology (2005) 66:3 222-230

89. Thompson CR, Iyer SS, Melrose N, Van Oosten R, Johnson K, Pitson SM, Obeid LM, Kusner DJ:

Sphingosine kinase 1 (SK1) is recruited to nascent phagosomes in human macrophages: inhibition of

SK1 translocation by Mycobacterium tuberculosis. Journal of Immunology (2005) 174:3551-3561.

90. Thompson, C and Powrie, F. Regulatory T cells. Current opinion in Pharmacology (2004) 4:4 298-414.

91. Till, S, Francis, J, Nouri-Aria, K and Durham, S. Mechanisms of immunotherapy. Journal of Allergy

and Clinical Immunology (2004) 113:6 1025-1034

92. Tonkin D, He J, Barbour G and Haskins K. Regulatory T cells prevent transfer of type 1 diabetes in

NOD mice only when their antigen is present in vivo. Journal of Immunology (2008) Oct 1; 181 (7):

4516-22

93. Uraushihara K, Kanai T, Ko K, Totsuka T, Makita S, Iiyama R, Nakamura T, Watanabe M. Regulation

of murine inflammatory bowel disease by CD25+ and CD25- CD4+ glucocorticoid-induced TNF

receptor family-related gene+ regulatory T cells.Journal of Immunology (2003) Jul 15;171(2):708-16.

70

94. Vieira, P, Christensen, J, Minaee, S, O’Neill, E, Barrats, F, Boonstra, A, Barthlott, T, Stockinger, B,

Wraith, D and O’Garra, A. IL-10-secreting regulatory T cell do not express FoxP3 but have

comparable regulatory function to naturally occurring CD4+CD25+ regulatory T cells. Journal of

Immunology 172 (2004) 5986-5993

95. Vigoroux S, Yvon E, Wagner H, BiagE, Dotti G, Silli U, Lira C, Rooney C and Brenner M. Induction

of antigen-specific regulatory T cells following overexpression of a Notch ligand by human B

lymphocytes. Journal of Virology (2003) 77:20 10872-10880

96. Walburger A, Koul A, Ferrari G, Nguyen L, Prescianotto-Baschong C, Huygen K, Klebl B, Thompson

C, Bacher G, Pieters J.Protein kinase G from pathogenic mycobacteria promotes survival within

macrophages.Science (2004) Jun 18;304(5678):1800-4

97. Walker PR, Ketunuti M, Choge IA, Meyers T, Gray G, Holmes EC, Morris L.Polymorphisms in Nef

associated with different clinical outcomes in HIV type 1 subtype C-infected children. AIDS Research

and Human Retroviruses. 2007 Feb;23(2):204-15.

98. Walther M, Tongren J, Andrews L, Korbel D, King E, Fletcher H, Andersen R, Bejon P, Thompson F,

Dunachie S, Edele F, De Souza J, Sinden R, Gilbert S, Riley E and Hill A. Upregulation of TGFβ,

FoxP3 and CD4+CD25+ regulatory T cells correlates with more rapid parasite growth in human

malaria infection. Immunity (2005) 23:3 287-296

99. Wing K, Onishi Y, Prieto-Martin P, Yamaguchi T, Miyara M, Fehervari Z, Nomura T, Sakaguchi S.

CTLA-4 control over Poxp3+ regulatory T cell function. Science (2008) Oct 01; 322 (5899): 271-5

100. Winkler B, Hufnagl K, Spittler A, Ploder M, Kállay E, Vrtala S, Valenta R, Kundi M, Renz H,

Wiedermann U. The role of Foxp3+ T cells in long-term efficacy of prophylactic and therapeutic

mucosal tolerance induced in mice Allergy. 2006 Feb;61(2):173-80.

101. Wolf D, Wolf A, Rumpold H, Fiegl H, Zeimet A, Muller-Holzner E, Deibl M, Gastl G, Gunsilius E

and Marth C. The expression of the regulatory T cell-specific forkhead box transcription factor FoxP3

is associated with poor prognosis in ovarian cancer. Clinical Cancer Research (2005) 1:11 8326-

8231

71

102. Yang, Z, Novak, A, Stenson, M, Witzig, T and Ansell, S. Intratumoral CD4+CD25+ regulatory T-

cell-mediated suppression of infiltrating CD4+T-cells in C-cell non-Hodgkin lymphoma. Blood 2006

May 1;107(9):3639-46.

103. Yong Z, Chang L, Mei YX, Yi L.Role and mechanisms of CD4+CD25+ regulatory T cells in the

induction and maintenance of transplantation tolerance.Transplant Immunology (2007)

Feb;17(2):120-9.